From noreply at r-forge.r-project.org  Wed Dec  3 11:45:38 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Wed,  3 Dec 2014 11:45:38 +0100 (CET)
Subject: [Vegan-commits] r2914 - in pkg/vegan: . R inst
Message-ID: <20141203104538.860511864EC@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-03 11:45:38 +0100 (Wed, 03 Dec 2014)
New Revision: 2914

Modified:
   pkg/vegan/NAMESPACE
   pkg/vegan/R/orditkplot.R
   pkg/vegan/inst/NEWS.Rd
Log:
Squashed commit of the following:

commit 53ba696282e13884d71c54143fdc07a368b26ec1
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Mon Dec 1 14:10:57 2014 +0200

    Do not import namespace of tcltk

    We need tcltk in one function (orditkplot) and DESCRIPTION only
    suggests the package. However, NAMESPACE has import(tcltk) and if
    tcltk is missing, loading vegan will fail. Now we omit tcltk import
    from the NAMESPACE, and orditkplot uses explicith tcltk:: prefix for
    all ca. 125 tcltk commands so that vegan can be used without tcltk
    package (except for orditlplot)

    I had seen this occasionally in some R builds, but the change was
    triggered by queries from Dave Roberts.

    (cherry picked from commit 2defbae459c0ca0b241dcc48442a4341e6c45564)

commit 099114797874ebb596ab7fb1b6fbebcae4af538c
Author: Gavin Simpson <ucfagls at gmail.com>
Date:   Sat Nov 22 19:40:24 2014 -0600

    use seq_along(x) instead of 1:length(x)

    (cherry picked from commit 2fa9b5d7725bd4dba44741dc607841058e17ff85)

commit 4232fab8f09f6ae37275aef7f9bc5b408953a109
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Tue Dec 2 18:46:03 2014 +0200

    NEWS on changes in 2.2-1

Modified: pkg/vegan/NAMESPACE
===================================================================
--- pkg/vegan/NAMESPACE	2014-11-24 10:44:01 UTC (rev 2913)
+++ pkg/vegan/NAMESPACE	2014-12-03 10:45:38 UTC (rev 2914)
@@ -77,7 +77,6 @@
 importFrom(tools, Rd2txt, startDynamicHelp)
 import(lattice)
 import(parallel)
-import(tcltk)
 importFrom(MASS, isoMDS, sammon, Shepard, mvrnorm)
 importFrom(cluster, daisy)
 ## 's' must be imported in mgcv < 1.8-0 (not needed later)

Modified: pkg/vegan/R/orditkplot.R
===================================================================
--- pkg/vegan/R/orditkplot.R	2014-11-24 10:44:01 UTC (rev 2913)
+++ pkg/vegan/R/orditkplot.R	2014-12-03 10:45:38 UTC (rev 2914)
@@ -13,7 +13,7 @@
 ############################
 ### Check and sanitize input
 ###########################
-    
+
     ## Graphical parameters and constants, and save some for later plotting
     p <- par()
     sparnam <- c("bg","cex", "cex.axis","cex.lab","col", "col.axis", "col.lab",
@@ -36,7 +36,7 @@
     }
     savepar <- p[sparnam]
     PPI <- 72                                         # Points per Inch
-    p2p <- as.numeric(tclvalue(tcl("tk", "scaling"))) # Pixel per point
+    p2p <- as.numeric(tcltk::tclvalue(tcltk::tcl("tk", "scaling"))) # Pixel per point
     DIAM <- 2.7                               # diam of plotting symbol
     ## Plotting symbol diam
     diam <- round(pcex * DIAM * p2p, 1)
@@ -47,7 +47,7 @@
         x <- gsub("transparent", "", x)
         x[is.na(x)] <- ""
         x
-    } 
+    }
     p$bg <- sanecol(p$bg)
     p$fg <- sanecol(p$fg)
     p$col <- sanecol(p$col)
@@ -86,13 +86,13 @@
                "0" = Point(x, y, 22, col, fill = "", diam),
                "1" = Point(x, y, 21, col, fill = "", diam),
                "2" = Point(x, y, 24, col, fill = "", diam),
-               "3" = {tkcreate(can, "line",
+               "3" = {tcltk::tkcreate(can, "line",
                                x, y+SQ*diam, x, y-SQ*diam, fill=col)
-                      tkcreate(can, "line",
+                      tcltk::tkcreate(can, "line",
                                x+SQ*diam, y, x-SQ*diam, y, fill=col)},
-               "4" = {tkcreate(can, "line",
+               "4" = {tcltk::tkcreate(can, "line",
                                x-diam, y-diam, x+diam, y+diam, fill=col)
-                      tkcreate(can, "line",
+                      tcltk::tkcreate(can, "line",
                                x-diam, y+diam, x+diam, y-diam, fill=col)},
                "5" = Point(x, y, 23, col, fill = "", diam),
                "6" = Point(x, y, 25, col, fill = "", diam),
@@ -110,9 +110,9 @@
                        Point(x, y, 0, col, fill, diam)},
                "13" = {Point(x, y, 4, col, fill, diam)
                        Point(x, y, 1, col, fill, diam)},
-               "14" = {tkcreate(can, "line", x-diam, y-diam, x, y+diam,
+               "14" = {tcltk::tkcreate(can, "line", x-diam, y-diam, x, y+diam,
                                 fill = col)
-                       tkcreate(can, "line", x+diam, y-diam, x, y+diam,
+                       tcltk::tkcreate(can, "line", x+diam, y-diam, x, y+diam,
                                 fill = col)
                        Point(x, y, 0, col, fill, diam)},
                "15" = Point(x, y, 22, col = col, fill = col, diam),
@@ -121,22 +121,22 @@
                "18" = Point(x, y, 23, col = col, fill = col, diam/SQ),
                "19" = Point(x, y, 21, col = col, fill = col, diam),
                "20" = Point(x, y, 21, col = col, fill = col, diam/2),
-               "21" = tkcreate(can, "oval", x-diam, y-diam,
+               "21" = tcltk::tkcreate(can, "oval", x-diam, y-diam,
                x+diam, y+diam, outline = col, fill = fill),
-               "22" = tkcreate(can, "rectangle", x-diam, y-diam,
+               "22" = tcltk::tkcreate(can, "rectangle", x-diam, y-diam,
                x+diam, y+diam, outline = col, fill = fill),
-               "23" = tkcreate(can, "polygon", x, y+SQ*diam,
+               "23" = tcltk::tkcreate(can, "polygon", x, y+SQ*diam,
                x+SQ*diam, y, x, y-SQ*diam, x-SQ*diam, y,
                outline = col, fill = fill),
-               "24" = tkcreate(can, "polygon", x, y-SQ*diam,
+               "24" = tcltk::tkcreate(can, "polygon", x, y-SQ*diam,
                x+sqrt(6)/2*diam, y+SQ/2*diam, x-sqrt(6)/2*diam, y+SQ/2*diam,
                outline = col, fill = fill),
-               "25" = tkcreate(can, "polygon", x, y+SQ*diam,
+               "25" = tcltk::tkcreate(can, "polygon", x, y+SQ*diam,
                x+sqrt(6)/2*diam, y-SQ/2*diam, x-sqrt(6)/2*diam, y-SQ/2*diam,
                outline = col, fill = fill),
                "o" = Point(x, y, 1, col, fill, diam),
                ## default: text with dummy location of the label
-               {tkcreate(can, "text",
+               {tcltk::tkcreate(can, "text",
                         x, y, text = as.character(pch), fill = col)
                 Point(x, y, 21, col="", fill="", diam)}
                 )
@@ -147,31 +147,33 @@
 ############################
 
     ## toplevel
-    w <- tktoplevel()
-    tktitle(w) <- deparse(match.call())
+    w <- tcltk::tktoplevel()
+    tcltk::tktitle(w) <- deparse(match.call())
     ## Max dim of windows (depends on screen)
-    YSCR <- as.numeric(tkwinfo("screenheight", w)) - 150
-    XSCR <- as.numeric(tkwinfo("screenwidth", w))
+    YSCR <- as.numeric(tcltk::tkwinfo("screenheight", w)) - 150
+    XSCR <- as.numeric(tcltk::tkwinfo("screenwidth", w))
 
 ################################
 ### Buttons and button functions
 ################################
 
     ## Buttons
-    buts <- tkframe(w)
+    buts <- tcltk::tkframe(w)
     ## Copy current canvas to EPS using the standard Tcl/Tk utility
-    cp2eps <- tkbutton(buts, text="Copy to EPS", 
-                       command=function() tkpostscript(can, x=0, y=0,
-                       height=height, width=width, 
-                       file=tkgetSaveFile(filetypes="{{EPS file} {.eps}}")))
-    dismiss <- tkbutton(buts, text="Dismiss", command=function() tkdestroy(w))
+    cp2eps <- tcltk::tkbutton(buts, text="Copy to EPS",
+                       command=function() tcltk::tkpostscript(can, x=0, y=0,
+                       height=height, width=width,
+                       file=tcltk::tkgetSaveFile(
+                         filetypes="{{EPS file} {.eps}}")))
+    dismiss <- tcltk::tkbutton(buts, text="Dismiss",
+                               command=function() tcltk::tkdestroy(w))
     ## Dump current plot to an "orditkplot" object (internally)
     ordDump <- function() {
         xy <- matrix(0, nrow=nrow(sco), ncol=2)
         rownames(xy) <- rownames(sco)
         colnames(xy) <- colnames(sco)
         for(nm in names(pola)) {
-            xy[as.numeric(tclvalue(id[[nm]])),] <- xy2usr(nm)
+            xy[as.numeric(tcltk::tclvalue(id[[nm]])),] <- xy2usr(nm)
         }
         curdim <- round(c(width, height) /PPI/p2p, 2)
         ## Sanitize colours for R plot
@@ -191,37 +193,37 @@
                    dim = curdim)
         class(xy) <- "orditkplot"
         xy
-    }        
+    }
     ## Button to dump "orditkplot" object to the R session
     pDump <- function() {
         xy <- ordDump()
-        dumpVar <- tclVar("")
-        tt <- tktoplevel()
-        tktitle(tt) <- "R Dump"
-        entryDump <- tkentry(tt, width=20, textvariable=dumpVar)
-        tkgrid(tklabel(tt, text="Enter name for an R object"))
-        tkgrid(entryDump, pady="5m")
+        dumpVar <- tcltk::tclVar("")
+        tt <- tcltk::tktoplevel()
+        tcltk::tktitle(tt) <- "R Dump"
+        entryDump <- tcltk::tkentry(tt, width=20, textvariable=dumpVar)
+        tcltk::tkgrid(tcltk::tklabel(tt, text="Enter name for an R object"))
+        tcltk::tkgrid(entryDump, pady="5m")
         isDone <- function() {
-            dumpName <- tclvalue(dumpVar)
+            dumpName <- tcltk::tclvalue(dumpVar)
             if (exists(dumpName, envir=.GlobalEnv)) {
-                ok <- tkmessageBox(message=paste(sQuote(dumpName),
+                ok <- tcltk::tkmessageBox(message=paste(sQuote(dumpName),
                                    "exists.\nOK to overwrite?"),
                                    icon="warning", type="okcancel",
                                    default="ok")
-                if(tclvalue(ok) == "ok") {
+                if(tcltk::tclvalue(ok) == "ok") {
                     assign(dumpName, xy, envir=.GlobalEnv)
-                    tkdestroy(tt)
+                    tcltk::tkdestroy(tt)
                 }
             }
             else {
                 assign(dumpName, xy, envir=.GlobalEnv)
-                tkdestroy(tt)
+                tcltk::tkdestroy(tt)
             }
         }
-        tkbind(entryDump, "<Return>", isDone)
-        tkfocus(tt)
+        tcltk::tkbind(entryDump, "<Return>", isDone)
+        tcltk::tkfocus(tt)
     }
-    dump <- tkbutton(buts, text="Dump to R", command=pDump)
+    dump <- tcltk::tkbutton(buts, text="Dump to R", command=pDump)
     ## Button to write current "orditkplot" object to a graphical device
     devDump <- function() {
         xy <- ordDump()
@@ -242,10 +244,10 @@
         if (!isTRUE(unname(capabilities("tiff"))))
             falt["tiff"] <- FALSE
         ftypes <- ftypes[falt]
-        fname <- tkgetSaveFile(filetypes=ftypes)
-        if(tclvalue(fname) == "")
+        fname <- tcltk::tkgetSaveFile(filetypes=ftypes)
+        if(tcltk::tclvalue(fname) == "")
             return(NULL)
-        fname <- tclvalue(fname)
+        fname <- tcltk::tclvalue(fname)
         ftype <- unlist(strsplit(fname, "\\."))
         ftype <- ftype[length(ftype)]
         if (ftype == "jpeg")
@@ -254,7 +256,7 @@
             ftype <- "tiff"
         mess <- "is not a supported type: file not produced. Supported types are"
         if (!(ftype %in% names(ftypes))) {
-            tkmessageBox(message=paste(sQuote(ftype), mess, paste(names(ftypes),
+            tcltk::tkmessageBox(message=paste(sQuote(ftype), mess, paste(names(ftypes),
                          collapse=", ")), icon="warning")
             return(NULL)
         }
@@ -272,19 +274,19 @@
         plot.orditkplot(xy)
         dev.off()
     }
-    export <- tkbutton(buts, text="Export plot", command=devDump)
+    export <- tcltk::tkbutton(buts, text="Export plot", command=devDump)
 
 ##########
 ### Canvas
 ##########
-    
+
     ## Make canvas
     sco <- try(scores(x, display=display, choices = choices, ...),
                silent = TRUE)
     if (inherits(sco, "try-error")) {
-        tkmessageBox(message=paste("No ordination scores were found in",
+        tcltk::tkmessageBox(message=paste("No ordination scores were found in",
                      sQuote(deparse(substitute(x)))), icon="error")
-        tkdestroy(w)
+        tcltk::tkdestroy(w)
         stop("argument x did not contain ordination scores")
     }
     if (!missing(labels))
@@ -325,13 +327,13 @@
         ylim <- range(sco[,2], na.rm = TRUE)
     xpretty <- pretty(xlim)
     ypretty <- pretty(ylim)
-    ## Extend ranges by 4% 
+    ## Extend ranges by 4%
     xrange <- c(-0.04, 0.04) * diff(xlim) + xlim
     xpretty <- xpretty[xpretty >= xrange[1] & xpretty <= xrange[2]]
     yrange <- c(-0.04, 0.04) * diff(ylim) + ylim
     ypretty <- ypretty[ypretty >= yrange[1] & ypretty <= yrange[2]]
     ## Canvas like they were in the default devices when I last checked
-    if (missing(width)) 
+    if (missing(width))
         width <- p$din[1]
     width <- width * PPI * p2p
     ## Margin row width also varies with platform and devices
@@ -350,11 +352,11 @@
     }
     ## User coordinates of an item
     xy2usr <- function(item) {
-        xy <- as.numeric(tkcoords(can, item))
-        x <- xy[1] 
-        y <- xy[2] 
-        x <- xrange[1] + (x - mar[2])/xincr 
-        y <- yrange[2] - (y - mar[3])/yincr 
+        xy <- as.numeric(tcltk::tkcoords(can, item))
+        x <- xy[1]
+        y <- xy[2]
+        x <- xrange[1] + (x - mar[2])/xincr
+        y <- yrange[2] - (y - mar[3])/yincr
         c(x,y)
     }
     ## Canvas x or y to user coordinates
@@ -368,49 +370,51 @@
     height <- round((diff(yrange)/diff(xrange)) * xusr)
     height <- height + mar[1] + mar[3]
     ## Canvas, finally
-    can <- tkcanvas(w, relief="sunken", width=width, height=min(height,YSCR),
+    can <- tcltk::tkcanvas(w, relief="sunken", width=width, height=min(height,YSCR),
                     scrollregion=c(0,0,width,height))
     if (p$bg != "")
-        tkconfigure(can, bg=p$bg)
-    yscr <- tkscrollbar(w, command = function(...) tkyview(can, ...))
-    tkconfigure(can, yscrollcommand = function(...) tkset(yscr, ...))
+        tcltk::tkconfigure(can, bg=p$bg)
+    yscr <- tcltk::tkscrollbar(w, command =
+                               function(...) tcltk::tkyview(can, ...))
+    tcltk::tkconfigure(can, yscrollcommand =
+                       function(...) tcltk::tkset(yscr, ...))
     ## Pack it up
-    tkpack(buts, side="bottom", fill="x", pady="2m")
-    tkpack(can, side="left", fill="x")
-    tkpack(yscr, side="right", fill="y")
-    tkgrid(cp2eps, export, dump, dismiss, sticky="s")
+    tcltk::tkpack(buts, side="bottom", fill="x", pady="2m")
+    tcltk::tkpack(can, side="left", fill="x")
+    tcltk::tkpack(yscr, side="right", fill="y")
+    tcltk::tkgrid(cp2eps, export, dump, dismiss, sticky="s")
     ## Box
     x0 <- usr2xy(c(xrange[1], yrange[1]))
     x1 <- usr2xy(c(xrange[2], yrange[2]))
-    tkcreate(can, "rectangle", x0[1], x0[2], x1[1], x1[2], outline = p$fg,
+    tcltk::tkcreate(can, "rectangle", x0[1], x0[2], x1[1], x1[2], outline = p$fg,
              width = p$lwd)
     ## Axes and ticks
     tl <-  -p$tcl * rpix     # -p$tcl * p$ps * p2p
     axoff <- p$mgp[3] * rpix
     tmp <- xpretty
-    for (i in 1:length(tmp)) {
+    for (i in seq_along(tmp)) {
         x0 <- usr2xy(c(xpretty[1], yrange[1]))
         x1 <- usr2xy(c(xpretty[length(xpretty)], yrange[1]))
-        tkcreate(can, "line", x0[1], x0[2]+axoff, x1[1], x1[2]+axoff,
+        tcltk::tkcreate(can, "line", x0[1], x0[2]+axoff, x1[1], x1[2]+axoff,
                  fill=p$fg)
         xx <- usr2xy(c(tmp[i], yrange[1]))
-        tkcreate(can, "line", xx[1], xx[2] + axoff, xx[1], xx[2]+tl+axoff,
-                 fill=p$fg)
-        tkcreate(can, "text", xx[1], xx[2] + rpix * p$mgp[2], anchor="n",
+        tcltk::tkcreate(can, "line", xx[1], xx[2] + axoff, xx[1],
+                        xx[2]+tl+axoff, fill=p$fg)
+        tcltk::tkcreate(can, "text", xx[1], xx[2] + rpix * p$mgp[2], anchor="n",
                  text=as.character(tmp[i]), fill=p$col.axis, font=fnt.axis)
     }
     xx <- usr2xy(c(mean(xrange), yrange[1]))
-    tkcreate(can, "text", xx[1], xx[2] + rpix * p$mgp[1],
+    tcltk::tkcreate(can, "text", xx[1], xx[2] + rpix * p$mgp[1],
              text=colnames(sco)[1], fill=p$col.lab, anchor="n", font=fnt.lab)
     tmp <- ypretty
-    for (i in 1:length(tmp)) {
+    for (i in seq_along(tmp)) {
         x0 <- usr2xy(c(xrange[1], tmp[1]))
         x1 <- usr2xy(c(xrange[1], tmp[length(tmp)]))
-        tkcreate(can, "line", x0[1]-axoff, x0[2], x1[1]-axoff, x1[2])
+        tcltk::tkcreate(can, "line", x0[1]-axoff, x0[2], x1[1]-axoff, x1[2])
         yy <- usr2xy(c(xrange[1], tmp[i]))
-        tkcreate(can, "line", yy[1]-axoff, yy[2], yy[1]-tl-axoff, yy[2],
+        tcltk::tkcreate(can, "line", yy[1]-axoff, yy[2], yy[1]-tl-axoff, yy[2],
                  fill=p$fg )
-        tkcreate(can, "text", yy[1] - rpix * p$mgp[2] , yy[2], anchor="e",
+        tcltk::tkcreate(can, "text", yy[1] - rpix * p$mgp[2] , yy[2], anchor="e",
                  text=as.character(tmp[i]), fill = p$col.axis, font=fnt.axis)
     }
     ## Points and labels
@@ -425,19 +429,19 @@
         lsco <- sco
         laboff <- round(p2p * p$ps/2 + diam + 1)
     }
-    pola <- tclArray()        # points
-    labtext <- tclArray()     # text
-    id <- tclArray()          # index
+    pola <- tcltk::tclArray()        # points
+    labtext <- tcltk::tclArray()     # text
+    id <- tcltk::tclArray()          # index
     for (i in 1:nrow(sco)) {
         xy <- usr2xy(sco[i,])
         item <- Point(xy[1], xy[2], pch = pch[i], col = pcol[i],
                       fill = pbg[i], diam = diam[i])
         xy <- usr2xy(lsco[i,])
         fnt <- c(labfam[i], labsize[i], saneslant(labfnt[i]))
-        lab <- tkcreate(can, "text", xy[1], xy[2]-laboff[i], text=labs[i],
+        lab <- tcltk::tkcreate(can, "text", xy[1], xy[2]-laboff[i], text=labs[i],
                         fill = tcol[i], font=fnt)
-        tkaddtag(can, "point", "withtag", item)
-        tkaddtag(can, "label", "withtag", lab)
+        tcltk::tkaddtag(can, "point", "withtag", item)
+        tcltk::tkaddtag(can, "label", "withtag", lab)
         pola[[lab]] <- item
         labtext[[lab]] <- labs[i]
         id[[lab]] <- i
@@ -446,29 +450,30 @@
 ##############################
 ### Mouse operations on canvas
 ##############################
-    
+
     ## Plotting and Moving
     ## Mouse enters a label
     pEnter <- function() {
-        tkdelete(can, "box")
-        hbox <- tkcreate(can, "rectangle", tkbbox(can, "current"),
+        tcltk::tkdelete(can, "box")
+        hbox <- tcltk::tkcreate(can, "rectangle",
+                                tcltk::tkbbox(can, "current"),
                          outline = "red", fill = "yellow")
-        tkaddtag(can, "box", "withtag", hbox)
-        tkitemraise(can, "current")
+        tcltk::tkaddtag(can, "box", "withtag", hbox)
+        tcltk::tkitemraise(can, "current")
     }
     ## Mouse leaves a label
     pLeave <- function() {
-        tkdelete(can, "box")
+        tcltk::tkdelete(can, "box")
     }
     ## Select label
     pDown <- function(x, y) {
         x <- as.numeric(x)
         y <- as.numeric(y)
-        tkdtag(can, "selected")
-        tkaddtag(can, "selected", "withtag", "current")
-        tkitemraise(can, "current")
-        p <- as.numeric(tkcoords(can,
-                                 pola[[tkfind(can, "withtag", "current")]]))
+        tcltk::tkdtag(can, "selected")
+        tcltk::tkaddtag(can, "selected", "withtag", "current")
+        tcltk::tkitemraise(can, "current")
+        p <- as.numeric(tcltk::tkcoords(can,
+                             pola[[tcltk::tkfind(can, "withtag", "current")]]))
         .pX <<- (p[1]+p[3])/2
         .pY <<- (p[2]+p[4])/2
         .lastX <<- x
@@ -478,40 +483,41 @@
     pMove <- function(x, y) {
         x <- as.numeric(x)
         y <- as.numeric(y)
-        tkmove(can, "selected", x - .lastX, y - .lastY)
-        tkdelete(can, "ptr")
-        tkdelete(can, "box")
+        tcltk::tkmove(can, "selected", x - .lastX, y - .lastY)
+        tcltk::tkdelete(can, "ptr")
+        tcltk::tkdelete(can, "box")
         .lastX <<- x
         .lastY <<- y
         ## xadj,yadj: adjust for canvas scrolling
-        xadj <- as.numeric(tkcanvasx(can, 0))
-        yadj <- as.numeric(tkcanvasy(can, 0))
-        hbox <- tkcreate(can, "rectangle", tkbbox(can, "selected"),
-                         outline = "red")
-        tkaddtag(can, "box", "withtag", hbox)
-        conn <- tkcreate(can, "line", .lastX + xadj, .lastY+yadj,
+        xadj <- as.numeric(tcltk::tkcanvasx(can, 0))
+        yadj <- as.numeric(tcltk::tkcanvasy(can, 0))
+        hbox <- tcltk::tkcreate(can, "rectangle",
+                                tcltk::tkbbox(can, "selected"),
+                                outline = "red")
+        tcltk::tkaddtag(can, "box", "withtag", hbox)
+        conn <- tcltk::tkcreate(can, "line", .lastX + xadj, .lastY+yadj,
                          .pX, .pY, fill="red")
-        tkaddtag(can, "ptr", "withtag", conn)
+        tcltk::tkaddtag(can, "ptr", "withtag", conn)
     }
     ## Edit label
     pEdit <- function() {
-        tkdtag(can, "selected")
-        tkaddtag(can, "selected", "withtag", "current")
-        tkitemraise(can, "current")
-        click <- tkfind(can, "withtag", "current")
-        txt <- tclVar(labtext[[click]])
+        tcltk::tkdtag(can, "selected")
+        tcltk::tkaddtag(can, "selected", "withtag", "current")
+        tcltk::tkitemraise(can, "current")
+        click <- tcltk::tkfind(can, "withtag", "current")
+        txt <- tcltk::tclVar(labtext[[click]])
         i <- as.numeric(id[[click]])
-        tt <- tktoplevel()
-        labEd <- tkentry(tt, width=20, textvariable=txt)
-        tkgrid(tklabel(tt, text = "Edit label"))
-        tkgrid(labEd, pady="5m", padx="5m")
+        tt <- tcltk::tktoplevel()
+        labEd <- tcltk::tkentry(tt, width=20, textvariable=txt)
+        tcltk::tkgrid(tcltk::tklabel(tt, text = "Edit label"))
+        tcltk::tkgrid(labEd, pady="5m", padx="5m")
         isDone <- function() {
-            txt <- tclvalue(txt)
-            tkitemconfigure(can, click, text = txt)
+            txt <- tcltk::tclvalue(txt)
+            tcltk::tkitemconfigure(can, click, text = txt)
             rownames(sco)[i] <<- txt
-            tkdestroy(tt)
+            tcltk::tkdestroy(tt)
         }
-        tkbind(labEd, "<Return>", isDone)
+        tcltk::tkbind(labEd, "<Return>", isDone)
     }
     ## Zooming: draw rectangle and take its user coordinates
     ## Rectangle: first corner
@@ -519,7 +525,7 @@
         x <- as.numeric(x)
         y <- as.numeric(y)
         ## yadj here and below adjusts for canvas scrolling
-        yadj <- as.numeric(tkcanvasy(can, 0))
+        yadj <- as.numeric(tcltk::tkcanvasy(can, 0))
         .pX <<- x
         .pY <<- y + yadj
     }
@@ -527,13 +533,13 @@
     pRect <- function(x, y) {
         x <- as.numeric(x)
         y <- as.numeric(y)
-        tkdelete(can, "box")
-        yadj <- as.numeric(tkcanvasy(can, 0))
+        tcltk::tkdelete(can, "box")
+        yadj <- as.numeric(tcltk::tkcanvasy(can, 0))
         .lastX <<- x
         .lastY <<- y + yadj
-        rect <- tkcreate(can, "rectangle", .pX, .pY, .lastX, .lastY,
+        rect <- tcltk::tkcreate(can, "rectangle", .pX, .pY, .lastX, .lastY,
                          outline="blue")
-        tkaddtag(can, "box", "withtag", rect)
+        tcltk::tkaddtag(can, "box", "withtag", rect)
     }
     ## Redraw ordiktplot with new xlim and ylim
     pZoom <- function() {
@@ -555,20 +561,21 @@
     .pY <- 0
     ## Mouse bindings:
     ## Moving a label
-    tkitembind(can, "label", "<Any-Enter>", pEnter)
-    tkitembind(can, "label", "<Any-Leave>", pLeave)
-    tkitembind(can, "label", "<1>", pDown)
-    tkitembind(can, "label", "<ButtonRelease-1>",
-               function() {tkdtag(can, "selected"); tkdelete(can, "ptr")})
-    tkitembind(can, "label", "<B1-Motion>", pMove)
+    tcltk::tkitembind(can, "label", "<Any-Enter>", pEnter)
+    tcltk::tkitembind(can, "label", "<Any-Leave>", pLeave)
+    tcltk::tkitembind(can, "label", "<1>", pDown)
+    tcltk::tkitembind(can, "label", "<ButtonRelease-1>",
+               function() {tcltk::tkdtag(can, "selected")
+                           tcltk::tkdelete(can, "ptr")})
+    tcltk::tkitembind(can, "label", "<B1-Motion>", pMove)
     ## Edit labels
-    tkitembind(can, "label", "<Double-Button-1>", pEdit) 
+    tcltk::tkitembind(can, "label", "<Double-Button-1>", pEdit)
     ## Zoom (with one-button mouse)
-    tkbind(can, "<Shift-Button-1>", pRect0)
-    tkbind(can, "<Shift-B1-Motion>", pRect)
-    tkbind(can, "<Shift-ButtonRelease>", pZoom)
+    tcltk::tkbind(can, "<Shift-Button-1>", pRect0)
+    tcltk::tkbind(can, "<Shift-B1-Motion>", pRect)
+    tcltk::tkbind(can, "<Shift-ButtonRelease>", pZoom)
     ## Zoom (with right button)
-    tkbind(can, "<Button-3>", pRect0)
-    tkbind(can, "<B3-Motion>", pRect)
-    tkbind(can, "<ButtonRelease-3>", pZoom)
+    tcltk::tkbind(can, "<Button-3>", pRect0)
+    tcltk::tkbind(can, "<B3-Motion>", pRect)
+    tcltk::tkbind(can, "<ButtonRelease-3>", pZoom)
 }

Modified: pkg/vegan/inst/NEWS.Rd
===================================================================
--- pkg/vegan/inst/NEWS.Rd	2014-11-24 10:44:01 UTC (rev 2913)
+++ pkg/vegan/inst/NEWS.Rd	2014-12-03 10:45:38 UTC (rev 2914)
@@ -2,6 +2,28 @@
 \title{vegan News}
 \encoding{UTF-8}
 
+\section{Changes in version 2.2-1}{
+
+  \subsection{BUG FIXES}{
+    \itemize{
+
+      \item \code{tolerance} function failed for unconstrained
+      correspondence analysis.
+
+    }
+  } % bug fixes
+
+  \subsection{NEW FEATURES}{
+    \itemize{
+
+      \item \code{linestack} accepts now expressions (such as
+      mathematical notation) as labels.
+
+    }
+  } % new features
+
+} % v2.2-1
+
 \section{Changes in version 2.2-0}{
 
   \subsection{GENERAL}{


From noreply at r-forge.r-project.org  Wed Dec  3 11:45:39 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Wed,  3 Dec 2014 11:45:39 +0100 (CET)
Subject: [Vegan-commits] r2915 - pkg/vegan/inst
Message-ID: <20141203104539.C29821874EA@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-03 11:45:39 +0100 (Wed, 03 Dec 2014)
New Revision: 2915

Modified:
   pkg/vegan/inst/NEWS.Rd
Log:
Merge branch 'cran-2.2' into r-forge-svn-local

Modified: pkg/vegan/inst/NEWS.Rd
===================================================================
--- pkg/vegan/inst/NEWS.Rd	2014-12-03 10:45:38 UTC (rev 2914)
+++ pkg/vegan/inst/NEWS.Rd	2014-12-03 10:45:39 UTC (rev 2915)
@@ -4,6 +4,16 @@
 
 \section{Changes in version 2.2-1}{
 
+  \subsection{INSTALLATION}{
+    \itemize{
+
+      \item \pkg{vegan} can be installed and loaded without \pkg{tcltk}
+      package. The \pkg{tcltk} package is needed in \code{orditkplot}
+      function for interactive editing of ordination graphics.
+
+    }
+  }
+
   \subsection{BUG FIXES}{
     \itemize{
 


From noreply at r-forge.r-project.org  Wed Dec  3 11:46:54 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Wed,  3 Dec 2014 11:46:54 +0100 (CET)
Subject: [Vegan-commits] r2916 - www
Message-ID: <20141203104654.E73B11874EA@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-03 11:46:54 +0100 (Wed, 03 Dec 2014)
New Revision: 2916

Modified:
   www/NEWS.html
Log:
Update NEWS


Modified: www/NEWS.html
===================================================================
--- www/NEWS.html	2014-12-03 10:45:39 UTC (rev 2915)
+++ www/NEWS.html	2014-12-03 10:46:54 UTC (rev 2916)
@@ -7,6 +7,47 @@
 
 <h2>vegan News</h2>
 
+<h3>Changes in version 2.2-1</h3>
+
+
+
+<h4>INSTALLATION</h4>
+
+
+<ul>
+<li> <p><span class="pkg">vegan</span> can be installed and loaded without <span class="pkg">tcltk</span>
+package. The <span class="pkg">tcltk</span> package is needed in <code>orditkplot</code>
+function for interactive editing of ordination graphics.
+</p>
+</li></ul>
+
+
+
+
+<h4>BUG FIXES</h4>
+
+
+<ul>
+<li> <p><code>tolerance</code> function failed for unconstrained
+correspondence analysis.
+</p>
+</li></ul>
+
+ 
+
+
+<h4>NEW FEATURES</h4>
+
+
+<ul>
+<li> <p><code>linestack</code> accepts now expressions (such as
+mathematical notation) as labels.
+</p>
+</li></ul>
+
+ 
+
+
 <h3>Changes in version 2.2-0</h3>
 
 


From noreply at r-forge.r-project.org  Mon Dec  8 09:47:24 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Mon,  8 Dec 2014 09:47:24 +0100 (CET)
Subject: [Vegan-commits] r2917 - pkg/vegan/R
Message-ID: <20141208084724.4CDCD1873ED@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-08 09:47:23 +0100 (Mon, 08 Dec 2014)
New Revision: 2917

Modified:
   pkg/vegan/R/as.hclust.spantree.R
   pkg/vegan/R/cophenetic.spantree.R
   pkg/vegan/R/lines.spantree.R
   pkg/vegan/R/plot.spantree.R
   pkg/vegan/R/spantree.R
Log:
Handle degenerate spantrees with two, one or zero points

(cherry picked from commit 8bc11fa94ca5ab17e007aaec30507505e377847c)

Modified: pkg/vegan/R/as.hclust.spantree.R
===================================================================
--- pkg/vegan/R/as.hclust.spantree.R	2014-12-03 10:46:54 UTC (rev 2916)
+++ pkg/vegan/R/as.hclust.spantree.R	2014-12-08 08:47:23 UTC (rev 2917)
@@ -12,7 +12,9 @@
 {
     ## Order by the lengths of spanning tree links
     o <- order(x$dist)
-    npoints <- length(o) + 1
+    npoints <- x$n
+    if(npoints < 2)
+        stop("needs at least two points")
     ## Ordered indices of dads and kids
     dad <- (2:npoints)[o]
     kid <- x$kid[o]

Modified: pkg/vegan/R/cophenetic.spantree.R
===================================================================
--- pkg/vegan/R/cophenetic.spantree.R	2014-12-03 10:46:54 UTC (rev 2916)
+++ pkg/vegan/R/cophenetic.spantree.R	2014-12-08 08:47:23 UTC (rev 2917)
@@ -1,8 +1,10 @@
-"cophenetic.spantree" <-
+`cophenetic.spantree` <-
     function(x)
 {
-    n <- length(x$kid) + 1
+    n <- x$n
     mat <- matrix(NA, nrow=n, ncol=n)
+    if (n < 2)
+        return(as.dist(mat))
     ind <- apply(cbind(2:n, x$kid), 1, sort)
     ind <- t(ind[2:1,])
     mat[ind] <- x$dist

Modified: pkg/vegan/R/lines.spantree.R
===================================================================
--- pkg/vegan/R/lines.spantree.R	2014-12-03 10:46:54 UTC (rev 2916)
+++ pkg/vegan/R/lines.spantree.R	2014-12-08 08:47:23 UTC (rev 2917)
@@ -1,9 +1,10 @@
-"lines.spantree" <-
+`lines.spantree` <-
     function (x, ord, display = "sites", ...)
 {
     ord <- scores(ord, display = display, ...)
     tree <- x$kid
-    ordiArgAbsorber(ord[-1, 1], ord[-1, 2], ord[tree, 1], ord[tree, 2],
-                   FUN = segments, ...)
+    if (x$n > 1)
+        ordiArgAbsorber(ord[-1, 1], ord[-1, 2], ord[tree, 1], ord[tree, 2],
+                        FUN = segments, ...)
     invisible()
 }

Modified: pkg/vegan/R/plot.spantree.R
===================================================================
--- pkg/vegan/R/plot.spantree.R	2014-12-03 10:46:54 UTC (rev 2916)
+++ pkg/vegan/R/plot.spantree.R	2014-12-08 08:47:23 UTC (rev 2917)
@@ -1,21 +1,24 @@
-"plot.spantree" <-
+`plot.spantree` <-
     function (x, ord, cex = 0.7, type = "p", labels, dlim, FUN = sammon, 
               ...) 
 {
     FUNname <- deparse(substitute(FUN))
     FUN <- match.fun(FUN)
-    n <- length(x$kid) + 1
+    n <- x$n
     if (missing(ord)) {
         d <- cophenetic(x)
         if (any(d<=0))
             d[d<=0] <- min(d>0)/10
         if (!missing(dlim)) 
             d[d > dlim ] <- dlim
-        y <- cmdscale(d)
-        dup <- duplicated(y)
-        if (any(dup))
-            y[dup, ] <- y[dup,] + runif(2*sum(dup), -0.01, 0.01) 
-        ord <- FUN(d, y)
+        if (n > 2) {
+            y <- cmdscale(d)
+            dup <- duplicated(y)
+            if (any(dup))
+            y[dup, ] <- y[dup,] + runif(2*sum(dup), -0.01, 0.01)
+            ord <- FUN(d, y)
+        } else
+            ord <- cbind(seq_len(n), rep(0,n))
     }
     ord <- scores(ord, display = "sites", ...)
     ordiArgAbsorber(ord, asp = 1, type = "n", FUN = "plot", ...)

Modified: pkg/vegan/R/spantree.R
===================================================================
--- pkg/vegan/R/spantree.R	2014-12-03 10:46:54 UTC (rev 2916)
+++ pkg/vegan/R/spantree.R	2014-12-08 08:47:23 UTC (rev 2917)
@@ -1,4 +1,4 @@
-"spantree" <-
+`spantree` <-
     function (d, toolong = 0) 
 {
     dis <- as.dist(d)
@@ -8,7 +8,7 @@
               n = as.integer(n), val = double(n + 1),
               dad = integer(n + 1), NAOK = TRUE, PACKAGE = "vegan")
     out <- list(kid = dis$dad[2:n] + 1, dist = dis$val[2:n],
-                labels = labels, call = match.call())
+                labels = labels, n = n, call = match.call())
     class(out) <- "spantree"
     out
 }


From noreply at r-forge.r-project.org  Fri Dec 12 09:42:59 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Fri, 12 Dec 2014 09:42:59 +0100 (CET)
Subject: [Vegan-commits] r2918 - in pkg/vegan: R vignettes
Message-ID: <20141212084259.42D0D1862D4@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-12 09:42:58 +0100 (Fri, 12 Dec 2014)
New Revision: 2918

Modified:
   pkg/vegan/R/estimateR.default.R
   pkg/vegan/R/specpool.R
   pkg/vegan/vignettes/diversity-vegan.Rnw
   pkg/vegan/vignettes/vegan.bib
Log:
Squashed commit of the following:

commit fd3ffc60c65f46f1c5554025ece18f2fd58cfda1
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Thu Dec 11 12:51:19 2014 +0200

    tweaks

    (cherry picked from commit 685e5795e02deb75c78803f2f1c2e82ef3c49663)

commit 66aca05f78de8dadb0cc7c9e978da59794726dd9
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Wed Dec 10 20:30:30 2014 +0200

    Edit diversity-vegan

    (cherry picked from commit 79eb46ece1cac5081f50d4bd84b0c4e8899b2b1c)

commit 2bc1a16c03f11d8886f4ed57ad391e7a5d851e32
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Sun Dec 7 19:04:14 2014 +0200

    Edit diversity-vegan vignette

    Be explicit about extended species richness only concerning
    the number of unseen species and not the total number of species.

    (cherry picked from commit b06ec8328d3083804d2a84ad4b74b67cab41d428)

commit ee9153e2ce44b179eb118611c0e6989e8bdd56bf
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Sun Dec 7 18:14:20 2014 +0200

    Use only the new "exact" variance estimator for Chao bias-reduced

    (cherry picked from commit 9e49c56035bd0ac91b4bd23f2900d57ba4361ff9)

commit 39f7e67a1c30ff84a6dd6263df950d2e7cbe075e
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Sun Dec 7 18:06:39 2014 +0200

    Document the exact Chao bia-corrected variance estimator

    (cherry picked from commit d8253316fc983d4d0ba5a2910a0079b8cffd8852)

commit b150c979190a9288d2aca2291aa50308dee40324
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Sun Dec 7 16:50:53 2014 +0200

    More exact derivation of approximate variance of bias-reduced Chao

    The common texts (and EstimateS web page) use approximate estimator
    for bias-corrected Chao estimate. This uses derivation for the basic
    estimator but replaces terms with those of bias corrected form
    (a1^2 -> a1*(a1-1), 2*a2 -> 2*(a2+1)). The used form is unpublished
    as such, but it follows exactly the derivation as given in Chiu et al.,
    web appendix. The numerical differences between forms are tiny: in
    BCI the maximum difference is ca. 0.02%, and in the 'mite' data up to
    12% -- it seems that difference vanishes as the sample size (no. of
    individuals) increases.

    (cherry picked from commit b7f92c6fb41288c3e441e14acc044bb0ce748e26)

commit e2332b369d9b7df79545819406336db3662202b7
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Thu Dec 4 20:28:49 2014 +0200

    Formatting of diversity vignette

    (cherry picked from commit d24db8b233328d961ea77c65e46f9531b5ee418e)

commit 1ed473db86678e0070de068dbe3324952386589d
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Thu Dec 4 17:14:40 2014 +0200

    Edit description of Chao estimates in the diversity vignette

    (cherry picked from commit d689ed87db134f5da95c24485a2f54e4847b7703)

commit 0b6e8af9c070084fba41e99c0578293e3f42de45
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Thu Dec 4 13:11:29 2014 +0200

    Use simpler expression for the variance of Chao extrapolation

    The new expression uses lower power or one multiplication less than
    the old one. The old one directly lifted from the literature, and
    it is mathematically equal to the new one.

    (cherry picked from commit 92db96cb09a3191add7464220777ca9cfcf97e27)

commit 3aef904857191eb6f69d840adb57254ff7c82253
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date:   Mon Dec 8 12:39:35 2014 +0200

    typo reported by Olivier Missa at ens.fr
    (cherry picked from commit 199131ed12c5c514223f8681121eabf6e516a6b2)

Modified: pkg/vegan/R/estimateR.default.R
===================================================================
--- pkg/vegan/R/estimateR.default.R	2014-12-08 08:47:23 UTC (rev 2917)
+++ pkg/vegan/R/estimateR.default.R	2014-12-12 08:42:58 UTC (rev 2918)
@@ -55,15 +55,26 @@
     ##else
     ##    S.Chao1 <- S.obs
     Deriv.Ch1 <- gradF(a, i)
-    ##if (a[2] > 0)
-    ##    sd.Chao1 <- sqrt(a[2] * (SSC * (SSC * (G^4/4 + G^3) + G^2/2)))
-    ##else if (a[1] > 0)
-    sd.Chao1 <-
-        sqrt(SSC*(a[1]*(a[1]-1)/2/(a[2]+1) +
-                  SSC*(a[1]*(2*a[1]-1)^2/4/(a[2]+1)^2 +
-                       a[1]^2*a[2]*(a[1]-1)^2/4/(a[2]+1)^4)))
-    ##else
-    ##    sd.Chao1 <- 0
+
+    ## The commonly used variance estimator is wrong for bias-reduced
+    ## Chao estimate. It is based on the variance estimator of basic
+    ## Chao estimate, but replaces the basic terms with corresponding
+    ## terms in the bias-reduced estimate. The following is directly
+    ## derived from the bias-reduced estimate.
+
+    ## The commonly used one (for instance, in EstimateS):
+    ##sd.Chao1 <-
+    ##    sqrt(SSC*(a[1]*(a[1]-1)/2/(a[2]+1) +
+    ##              SSC*(a[1]*(2*a[1]-1)^2/4/(a[2]+1)^2 +
+    ##                  a[1]^2*a[2]*(a[1]-1)^2/4/(a[2]+1)^4)))
+
+    sd.Chao1 <- (a[1]*((-a[2]^2+(-2*a[2]-a[1])*a[1])*a[1] +
+                       (-1+(-4+(-5-2*a[2])*a[2])*a[2] +
+                        (-2+(-1+(2*a[2]+2)*a[2])*a[2] +
+                         (4+(6+4*a[2])*a[2] + a[1]*a[2])*a[1])*a[1])*S.Chao1))/
+                             4/(a[2]+1)^4/S.Chao1
+    sd.Chao1 <- sqrt(sd.Chao1)
+
     C.ace <- 1 - a[1]/N.rare
     i <- 1:length(a)
     thing <- i * (i - 1) * a
@@ -72,7 +83,7 @@
     S.ACE <- S.abund + S.rare/C.ace + max(Gam, 0) * a[1]/C.ace
     sd.ACE <- sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - 
                                                      a %*% t(a)/S.ACE)))
-    out <- list(S.obs = S.obs, S.chao1 = S.Chao1, se.chao1 = sd.Chao1, 
+    out <- list(S.obs = S.obs, S.chao1 = S.Chao1, se.chao1 = sd.Chao1,
                 S.ACE = S.ACE, se.ACE = sd.ACE)
     out <- unlist(out)
     out

Modified: pkg/vegan/R/specpool.R
===================================================================
--- pkg/vegan/R/specpool.R	2014-12-08 08:47:23 UTC (rev 2917)
+++ pkg/vegan/R/specpool.R	2014-12-12 08:42:58 UTC (rev 2918)
@@ -52,7 +52,7 @@
             a1/a2
         else 0
         if (a2 > 0)
-            var.chao[is] <- a2 * ssc * (0.5 + ssc * (1 + aa/4) * aa) * aa * aa
+            var.chao[is] <- a1 * ssc * (0.5 + ssc * (1 + aa/4) * aa) * aa
         else
             var.chao[is] <-
                 ssc * (ssc * (a1*(2*a1-1)^2/4 - a1^4/chao[is]/4) + a1*(a1-1)/2)

Modified: pkg/vegan/vignettes/diversity-vegan.Rnw
===================================================================
--- pkg/vegan/vignettes/diversity-vegan.Rnw	2014-12-08 08:47:23 UTC (rev 2917)
+++ pkg/vegan/vignettes/diversity-vegan.Rnw	2014-12-12 08:42:58 UTC (rev 2918)
@@ -103,8 +103,8 @@
 \begin{equation}
   H_q = \frac{1}{q-1} \left(1 - \sum_{i=1}^S p^q \right) \, .
 \end{equation}
-This corresponds to common diversity indices: $H_0 = S-1$, $H_1 = H'$,
-and $H_2 = D_2$, and can be converted to the Hill number:
+These correspond to common diversity indices: $H_0 = S-1$, $H_1 = H'$,
+and $H_2 = D_1$, and can be converted to Hill numbers:
 \begin{equation}
   N_q = (1 - (q-1) H_q )^\frac{1}{1-q} \, .
 \end{equation}
@@ -572,66 +572,90 @@
 species is related to the number of rare species, or species seen only
 once or twice.
 
+The incidence-based functions group species by their number of
+occurrences $f_i = f_0, f_1, \ldots, f_N$, where $f$ is the number of
+species occuring in exactly $i$ sites in the data: $f_N$ is the number
+of species occurring on every $N$ site, $f_1$ the number of species
+occurring once, and $f_0$ the number of species in the species pool
+but not found in the sample. The total number of species in the pool
+$S_p$ is
+\begin{equation}
+S_p = \sum_{i=0}^N f_i = f_0+ S_o \,,
+\end{equation}
+where $S_o = \sum_{i>0} f_i$ is the observed number of species.  The
+sampling proportion $i/N$ is an estimate for the commonness of the
+species in the community. When species is present in the community but
+not in the sample, $i=0$ is an obvious under-estimate, and
+consequently, for values $i>0$ the species commonness is
+over-estimated \citep{Good53}. The models for the pool size estimate
+the number of species missing in the sample $f_0$.
+
 Function \code{specpool} implements the following models to estimate
-the pool size $S_p$ \citep{SmithVanBelle84, Chao87, ChiuEtal14}:
+the number of missing species $f_0$. Chao estimator  is \citep{Chao87, ChiuEtal14}:
+\begin{equation}
+\label{eq:chao}
+\hat f_0 = \begin{cases} 
+    \frac{f_1^2}{2 f_2} \frac{N-1}{N} &\text{if } f_2 > 0 \\
+\frac{f_1 (f_1 -1)}{2}  \frac{N-1}{N} & \text{if } f_2 = 0
+\end{cases}
+\end{equation}
+The latter case for $f_2=0$ is known as the bias-corrected
+form. \citet{ChiuEtal14} introduced the small-sample correction term
+$\frac{N}{N-1}$, but it was not originally used \citep{Chao87}.
+
+The first and second order jackknife estimators are
+\citep{SmithVanBelle84}:
 \begin{align}
-\label{eq:chao-basic}
-S_p &= S_o + \frac{f_1^2}{2 f_2} \frac{N-1}{N} & \text{Chao}\\
-\label{eq:chao-bc}
-S_p &= S_o + \frac{f_1 (f_1 -1)}{2 (f_2+1)}  \frac{N-1}{N} & \text{Chao bias-corrected}\\
-S_p &= S_o + f_1 \frac{N-1}{N}  & \text{1st order Jackknife}\\
-S_p & = S_o + f_1 \frac{2N-3}{N} \nonumber \\ & + f_2 \frac{(N-2)^2}{N(N-1)}
-& \text{2nd order Jackknife}\\
-S_p &= S_o + \sum_{i=1}^{S_o} (1-p_i)^N & \text{Bootstrap}
+\hat f_0 &=  f_1 \frac{N-1}{N}  \\ 
+\hat f_0 & =  f_1 \frac{2N-3}{N}  + f_2 \frac{(N-2)^2}{N(N-1)}
 \end{align}
-Here $S_o$ is the observed number of species, $f_1$ and $f_2$ are the
-numbers of species observed once or twice, $N$ is the number of sites,
-and $p_i$ are proportions of species.  The idea in jackknife seems to
-be that we missed about as many species as we saw only once, and the
-idea in bootstrap that if we repeat sampling (with replacement) from
-the same data, we miss as many species as we missed originally.
-\citet{ChiuEtal14} introduced the small-sample correction term
-$\frac{N}{N-1}$, but it was not originally used \citep{Chao87}.
+The boostrap estimator is \citep{SmithVanBelle84}:
+\begin{equation}
+\hat f_0 =  \sum_{i=1}^{S_o} (1-p_i)^N
+\end{equation}
+The idea in jackknife seems to be that we missed about as many species
+as we saw only once, and the idea in bootstrap that if we repeat
+sampling (with replacement) from the same data, we miss as many
+species as we missed originally.
 
-The variance the estimator of the basic Chao estimate is \citep{ChiuEtal14}:
+The variance estimaters only concern the estimated number of missing
+species $\hat f_0$, although they are often expressed as they would
+apply to the pool size $S_p$; this is only true if we assume that
+$\VAR(S_o) = 0$.  The variance of the Chao estimate is \citep{ChiuEtal14}:
 \begin{multline}
 \label{eq:var-chao-basic}
-s^2 = f_2 \left(A^2 \frac{G^4}{4} + A^2 G^3 + A \frac{G^2}{2} \right),\\
+\VAR(\hat f_0) = f_1 \left(A^2 \frac{G^3}{4} + A^2 G^2 + A \frac{G}{2} \right),\\
 \text{where}\; A = \frac{N-1}{N}\;\text{and}\; G = \frac{f_1}{f_2} 
 \end{multline}
-The variance of bias-corrected Chao estimate can be approximated by
-replacing the terms of eq.~\ref{eq:var-chao-basic} with the
-corresponding terms in eq.~\ref{eq:chao-bc}:
-\begin{multline}
-\label{eq:var-chao-bc}
-s^2 = A \frac{f_1(f_1-1)}{2(f_2+1)} + A^2 \frac{f_1(2 f_1+1)^2}{(f_2+1)^2}\\
- + A^2 \frac{f_1^2 f_2 (f_1 -1)^2}{4 (f_2 + 1)^4}
-\end{multline}
-If we apply the bias-correction in the special case where there are no
-doubletons ($f_2 = 0$), the he variance is 
+%% The variance of bias-corrected Chao estimate can be approximated by
+%% replacing the terms of eq.~\ref{eq:var-chao-basic} with the
+%% corresponding terms of the bias-correcter form of in eq.~\ref{eq:chao}:
+%% \begin{multline}
+%% \label{eq:var-chao-bc}
+%% s^2 = A \frac{f_1(f_1-1)}{2} + A^2 \frac{f_1(2 f_1+1)^2}{(f_2+1)^2}\\
+%%  + A^2 \frac{f_1^2 f_2 (f_1 -1)^2}{4 (f_2 + 1)^4}
+%% \end{multline}
+For the bias-corrected form of eq.~\ref{eq:chao}  (case $f_2 = 0$), the he variance is 
 \citep[who omit small-sample correction in some terms]{ChiuEtal14}:
 \begin{multline}
 \label{eq:var-chao-bc0}
-s^2 = \frac{1}{4} A^2 f_1 (2f_1 -1)^2 + \frac{1}{2} A f_1 (f_1-1) - \frac{1}{4}A^2 \frac{f_1^4}{S_p}
+\VAR(\hat f_0) = \frac{1}{4} A^2 f_1 (2f_1 -1)^2 + \frac{1}{2} A f_1 (f_1-1) - \frac{1}{4}A^2 \frac{f_1^4}{S_p}
 \end{multline}
-Function \code{specpool} uses eq.~\ref{eq:chao-basic} and estimates
-its variance with eq.~\ref{eq:var-chao-basic} when $f_2 > 0$. When
-$f_2 = 0$, \code{specpool} applies eq.~\ref{eq:chao-bc} which reduces
-to $\frac{N-1}{N} \frac{1}{2} f_1 (f_1 - 1)$, and its variance
-estimator eq.~\ref{eq:var-chao-bc0}.
 
 The variance of the first-order jackknife is based on the number of
 ``singletons'' $r$ (species occurring only once in the data) in sample
 plots \citep{SmithVanBelle84}:
 \begin{equation}
-s^2 = \left(\sum_{i=1}^N r_i^2 - \frac{f_1}{N}\right) \frac{N-1}{N}
+\VAR(\hat f_0) = \left(\sum_{i=1}^N r_i^2 - \frac{f_1}{N}\right) \frac{N-1}{N}
 \end{equation}
 Variance of the second-order jackknife is not evaluated in
 \code{specpool} (but contributions are welcome).
-For the variance of bootstrap estimator, it is practical to define a
-new variable $q_i = (1-p_i)^N$ for each species \citep{SmithVanBelle84}:
+
+The variance of bootstrap estimator is\citep{SmithVanBelle84}:
 \begin{multline}
-s^2 = \sum_{i=1}^{S_o} q_i (1-q_i)  \\ +2 \sum_{i \neq j}^{S_o} \left[(Z_{ij}/N)^N - q_i q_j \right]
+\VAR(\hat f_0) = \sum_{i=1}^{S_o} q_i (1-q_i)  \\ +2 \sum_{i \neq
+  j}^{S_o} \left[(Z_{ij}/N)^N - q_i q_j \right] \\
+\text{where } q_i = (1-p_i)^N \, ,
 \end{multline}
 where $Z_{ij}$ is the number of sites where both species are absent.
 
@@ -658,12 +682,40 @@
 <<>>=
 estimateR(BCI[k,])
 @ 
+In abundance based models $a_i$ denotes the number of species with $i$
+individuals, and takes the place of $f_i$ of previous models.
 Chao's method is similar as the bias-corrected model
-eq.~\ref{eq:chao-bc} with its variance estimator
-eq.~\ref{eq:var-chao-bc}, but it uses counts of individuals instead of
-incidences, and does not use small sample correction.  \textsc{ace} is
-based on rare species also:
+eq.~\ref{eq:chao} \citep{Chao87, ChiuEtal14}:
 \begin{equation}
+  \label{eq:chao-bc}
+  S_p = S_o + \frac{a_1 (a_1 - 1)}{2 (a_2 + 1)}\,.
+\end{equation}
+When $f_2=0$, eq.~\ref{eq:chao-bc} reduces to the bias-corrected form
+of eq.~\ref{eq:chao}, but quantitative estimators are based on
+abundances and do not use small-sample correction. This is not usually
+needed because sample sizes are total numbers of individuals, and
+these are usually high, unlike in frequency based models, where the
+sample size is the number of sites \citep{ChiuEtal14}. 
+
+A commonly used approximate variance estimator of eq.~\ref{eq:chao-bc} is:
+\begin{multline}
+  \label{eq:var-chao-bc}
+ s^2 = \frac{a_1(a_1-1)}{2} + \frac{a_1(2 a_1+1)^2}{(a_2+1)^2}\\
+  + \frac{a_1^2 a_2 (a_1 -1)^2}{4 (a_2 + 1)^4}
+\end{multline}
+However, \pkg{vegan} does not use this, but instead the following more
+exact form which was directly derived from eq.~\ref{eq:chao-bc}
+following \citet[web appendix]{ChiuEtal14}:
+\begin{multline}
+  s^2 = \frac{1}{4} \frac{1}{(a_2+1)^4 S_p} [a_1 (S_p a_1^3
+      a_2 + 4 S_p a_1^2 a_2^2 \\+  2 S_p a_1 a_2^3 + 6 S_p a_1^2 a_2 + 2 S_p
+      a_1 a_2^2 -2 S_p a_2^3 \\+ 4 S_p a_1^2 + S_p a_1 a_2 -5 S_p a_2^2 - a_1^3 - 2
+      a_1^2 a_2\\ - a_1 a_2^2 - 2 S_p a_1 - 4 S_p a_2 - S_p ) ]\,.
+\end{multline}
+The variance estimators only concern the number of unseen species like previously.
+
+The \textsc{ace} is estimator is defined as \citep{OHara05}:
+\begin{equation}
 \begin{split}
 S_p &= S_\mathrm{abund} + \frac{S_\mathrm{rare}}{C_\mathrm{ACE}} +
 \frac{a_1}{C_\mathrm{ACE}} \gamma^2\, , \quad \text{where}\\
@@ -677,7 +729,9 @@
 Here $S_\mathrm{abund}$ and $S_\mathrm{rare}$ are the numbers of
 species of abundant and rare species, with an arbitrary upper limit of
 10 individuals for a rare species, and $N_\mathrm{rare}$ is the total
-number of individuals in rare species.
+number of individuals in rare species. The variance estimator uses
+iterative solution, and it is best interpreted from the source code or
+following \citet{OHara05}.
 
 The pool size
 is estimated separately for each site, but if input is a data frame,

Modified: pkg/vegan/vignettes/vegan.bib
===================================================================
--- pkg/vegan/vignettes/vegan.bib	2014-12-08 08:47:23 UTC (rev 2917)
+++ pkg/vegan/vignettes/vegan.bib	2014-12-12 08:42:58 UTC (rev 2918)
@@ -1,4 +1,22 @@
 
+ at Article{OHara05,
+  author =	 {R. B. O'Hara},
+  title =	 {Species richness estimators: how many species can
+                  dance on the head of a pin},
+  journal =	 {Journal of Animal Ecology},
+  year =	 2005,
+  volume =	 74,
+  pages =	 {375--386}}
+
+ at Article{Good53,
+  author =	 {I. J. Good},
+  title =	 {The population frequencies of species and the
+                  estimation of population parameters},
+  journal =	 {Biometrika},
+  year =	 1953,
+  volume =	 40,
+  pages =	 {237--264}}
+
 @Article{ChiuEtal14,
   author =	 {C. H. Chiu and Y. T. Wang and B. A. Walther and
                   A. Chao},


From noreply at r-forge.r-project.org  Fri Dec 12 09:59:36 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Fri, 12 Dec 2014 09:59:36 +0100 (CET)
Subject: [Vegan-commits] r2919 - pkg/vegan/inst
Message-ID: <20141212085936.A0FA5187874@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-12 09:59:36 +0100 (Fri, 12 Dec 2014)
New Revision: 2919

Modified:
   pkg/vegan/inst/NEWS.Rd
Log:
NEWS about new variance estimator for Chao in estimateR

Modified: pkg/vegan/inst/NEWS.Rd
===================================================================
--- pkg/vegan/inst/NEWS.Rd	2014-12-12 08:42:58 UTC (rev 2918)
+++ pkg/vegan/inst/NEWS.Rd	2014-12-12 08:59:36 UTC (rev 2919)
@@ -26,9 +26,18 @@
   \subsection{NEW FEATURES}{
     \itemize{
 
-      \item \code{linestack} accepts now expressions (such as
-      mathematical notation) as labels.
+      \item \code{estimateR} uses a more exact variance formula for
+      bias-corrected Chao estimate of extrapolated number of
+      species. The new formula may be unpublished, but it was derived
+      following the guidelines of Chiu, Wang, Walther & Chao,
+      \emph{Biometrics} 70, 671--682 (2014),
+      \href{http://onlinelibrary.wiley.com/doi/10.1111/biom.12200/suppinfo}{online
+      supplementary material}.
 
+      \item \code{linestack} accepts now expressions as labels. This
+      allows using mathematical symbols and formula given as
+      mathematical expressions.
+
     }
   } % new features
 


From noreply at r-forge.r-project.org  Fri Dec 12 10:01:27 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Fri, 12 Dec 2014 10:01:27 +0100 (CET)
Subject: [Vegan-commits] r2920 - www
Message-ID: <20141212090127.F260318787A@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-12 10:01:27 +0100 (Fri, 12 Dec 2014)
New Revision: 2920

Modified:
   www/NEWS.html
Log:
update NEWS.html


Modified: www/NEWS.html
===================================================================
--- www/NEWS.html	2014-12-12 08:59:36 UTC (rev 2919)
+++ www/NEWS.html	2014-12-12 09:01:27 UTC (rev 2920)
@@ -1,9 +1,10 @@
-<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: vegan News</title>
-<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
-<link rel="stylesheet" type="text/css" href="R.css" />
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: vegan News</title>
+<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
+<link rel="stylesheet" type="text/css" href="R.css">
 </head><body>
 
-<table width="100%" summary="page for NEWS"><tr><td>NEWS</td><td style="text-align: right;">R Documentation</td></tr></table>
+<table width="100%" summary="page for NEWS"><tr><td>NEWS</td><td align="right">R Documentation</td></tr></table>
 
 <h2>vegan News</h2>
 
@@ -40,9 +41,19 @@
 
 
 <ul>
-<li> <p><code>linestack</code> accepts now expressions (such as
-mathematical notation) as labels.
+<li> <p><code>estimateR</code> uses a more exact variance formula for
+bias-corrected Chao estimate of extrapolated number of
+species. The new formula may be unpublished, but it was derived
+following the guidelines of Chiu, Wang, Walther &amp; Chao,
+<EM>Biometrics</EM> 70, 671&ndash;682 (2014),
+<a href="http://onlinelibrary.wiley.com/doi/10.1111/biom.12200/suppinfo">online
+supplementary material</a>.
 </p>
+</li>
+<li> <p><code>linestack</code> accepts now expressions as labels. This
+allows using mathematical symbols and formula given as
+mathematical expressions.
+</p>
 </li></ul>
 
  
@@ -69,7 +80,7 @@
 be used both in Windows and in unix-alikes. <span class="pkg">Vegan</span> vignette
 on Design decision explains the implementation (use
 <code>vegandocs("decission")</code>, and <span class="pkg">parallel</span> package has more
-extensive documentation on parallel processing in <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>.
+extensive documentation on parallel processing in <font face="Courier New,Courier" color="#666666"><b>R</b></font>.
 </p>
 <p>The following function use parallel processing in analysing
 permutation statistics: <code>adonis</code>, <code>anosim</code>,
@@ -132,7 +143,7 @@
 
 <ul>
 <li> <p><span class="pkg">vegan</span> package dependencies and namespace imports
-were adapted to changes in <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>, and no more trigger warnings and
+were adapted to changes in <font face="Courier New,Courier" color="#666666"><b>R</b></font>, and no more trigger warnings and
 notes in package tests.
 </p>
 </li>
@@ -151,7 +162,7 @@
 
 <ul>
 <li><p> Function <code>dispweight</code> implements dispersion weighting
-of Clarke et al. (<em>Marine Ecology Progress Series</em>, 320,
+of Clarke et al. (<EM>Marine Ecology Progress Series</EM>, 320,
 11&ndash;27).  In addition, we implemented a new method for
 generalized dispersion weighting <code>gdispweight</code>. Both
 methods downweight species that are significantly
@@ -161,7 +172,7 @@
 <li><p> New <code>hclust</code> support functions <code>reorder</code>,
 <code>rev</code> and <code>scores</code>. Functions <code>reorder</code> and
 <code>rev</code> are similar as these functions for <code>dendrogram</code>
-objects in base <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>. However, <code>reorder</code> can use (and defaults
+objects in base <font face="Courier New,Courier" color="#666666"><b>R</b></font>. However, <code>reorder</code> can use (and defaults
 to) weighted mean. In weighted mean the node average is always the
 mean of member leaves, whereas the <code>dendrogram</code> uses always
 unweighted means of joined branches.
@@ -177,7 +188,7 @@
 <li><p> Function <code>permustats</code> extracts and inspects permutation
 results with support functions <code>summary</code>, <code>density</code>,
 <code>densityplot</code>, <code>qqnorm</code> and <code>qqmath</code>. The
-<code>density</code> and <code>qqnorm</code> are standard <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> tools that only
+<code>density</code> and <code>qqnorm</code> are standard <font face="Courier New,Courier" color="#666666"><b>R</b></font> tools that only
 work with one statistic, and <code>densityplot</code> and <code>qqmath</code>
 are <span class="pkg">lattice</span> graphics that work with univariate and
 multivariate statistics. The results of following functions can be
@@ -298,7 +309,7 @@
 </li>
 <li><p> Functions for extrapolated number of species or for the size
 of species pool using Chao method were modified following Chiu et
-al., <em>Biometrics</em> 70, 671&ndash;682 (2014).
+al., <EM>Biometrics</EM> 70, 671&ndash;682 (2014).
 </p>
 <p>Incidence based <code>specpool</code> can now use (and defaults to)
 small sample correction with number of sites as the sample
@@ -342,7 +353,7 @@
 III.  <code>varespec</code> and <code>dune</code> use 8-character names (4
 from genus + 4 from species epithet). New data set on
 phylogenetic distances for <code>dune</code> was extracted from Zanne
-et al. (<em>Nature</em> 506, 89&ndash;92; 2014).
+et al. (<EM>Nature</EM> 506, 89&ndash;92; 2014).
 </p>
 </li>
 <li><p> User configurable plots for <code>rarecurve</code>.
@@ -474,11 +485,11 @@
 
 <ul>
 <li><p> This version is released due to changes in programming
-interface and testing procedures in <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> 3.0.2. If you are using an
-older version of <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>, there is no need to upgrade <span class="pkg">vegan</span>. There
+interface and testing procedures in <font face="Courier New,Courier" color="#666666"><b>R</b></font> 3.0.2. If you are using an
+older version of <font face="Courier New,Courier" color="#666666"><b>R</b></font>, there is no need to upgrade <span class="pkg">vegan</span>. There
 are no new features nor bug fixes. The only user-visible changes
 are in documentation and in output messages and formatting. Because
-of <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> changes, this version is dependent on <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> version 2.14.0
+of <font face="Courier New,Courier" color="#666666"><b>R</b></font> changes, this version is dependent on <font face="Courier New,Courier" color="#666666"><b>R</b></font> version 2.14.0
 or newer and on <span class="pkg">lattice</span> package.
 </p>
 </li></ul>
@@ -494,7 +505,7 @@
 
 <ul>
 <li><p> This is a maintenance release that fixes some issues
-raised by changed in <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> toolset for processing vignettes.  In
+raised by changed in <font face="Courier New,Courier" color="#666666"><b>R</b></font> toolset for processing vignettes.  In
 the same we also fix some typographic issues in the vignettes.
 </p>
 </li></ul>
@@ -540,7 +551,7 @@
 
 <ul>
 <li> <p><code>tabasco()</code> is a new function for graphical display
-of community data matrix.  Technically it is an interface to <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>
+of community data matrix.  Technically it is an interface to <font face="Courier New,Courier" color="#666666"><b>R</b></font>
 <code>heatmap</code>, but its use is closer to <span class="pkg">vegan</span> function
 <code>vegemite</code>. The function can reorder the community data
 matrix similarly as <code>vegemite</code>, for instance, by ordination
@@ -729,7 +740,7 @@
 <code>plot</code> etc. of the results. These methods are only used if
 the full <code>wcmdscale</code> result is returned with, e.g., argument
 <code>eig = TRUE</code>. The default is still to return only a matrix of
-scores similarly as the standard <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> function <code>cmdscale()</code>,
+scores similarly as the standard <font face="Courier New,Courier" color="#666666"><b>R</b></font> function <code>cmdscale()</code>,
 and in that case the new methods are not used.
 </p>
 </li></ul>
@@ -828,13 +839,13 @@
 version of LaTeX (TeXLive 2012).
 </p>
 </li>
-<li> <p><span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> versions later than 2.15-1 (including development
+<li> <p><font face="Courier New,Courier" color="#666666"><b>R</b></font> versions later than 2.15-1 (including development
 version) report warnings and errors when installing and checking
 <span class="pkg">vegan</span>, and you must upgrade <span class="pkg">vegan</span> to this version.
 The warnings concern functions <code>cIndexKM</code> and
 <code>betadisper</code>, and the error occurs in <code>betadisper</code>.
 These errors and warnings were triggered by internal changes in
-<span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>.
+<font face="Courier New,Courier" color="#666666"><b>R</b></font>.
 </p>
 </li></ul>
 
@@ -965,8 +976,8 @@
 <li><p> Added new nestedness functions <code>nestedbetasor</code> and
 <code>nestedbetajac</code> that implement multiple-site dissimilarity
 indices and their decomposition into turnover and nestedness
-components following Baselga (<em>Global Ecology and
-Biogeography</em> 19, 134&ndash;143; 2010).
+components following Baselga (<EM>Global Ecology and
+Biogeography</EM> 19, 134&ndash;143; 2010).
 </p>
 </li>
 <li><p> Added function <code>rarecurve</code> to draw rarefaction curves
@@ -976,8 +987,8 @@
 </p>
 </li>
 <li><p> Added function <code>simper</code> that implements
-&ldquo;similarity percentages&rdquo; of Clarke (<em>Australian
-Journal of Ecology</em> 18, 117&ndash;143; 1993).  The method compares
+&ldquo;similarity percentages&rdquo; of Clarke (<EM>Australian
+Journal of Ecology</EM> 18, 117&ndash;143; 1993).  The method compares
 two or more groups and decomposes the average between-group
 Bray-Curtis dissimilarity index to contributions by individual
 species.  The code was developed in 
@@ -1049,8 +1060,8 @@
 </p>
 </li>
 <li><p> Added Cao dissimilarity (CYd) as a new dissimilarity
-method in <code>vegdist</code> following Cao et al., <em>Water
-Envir Res</em> 69, 95&ndash;106 (1997). The index should be good for
+method in <code>vegdist</code> following Cao et al., <EM>Water
+Envir Res</EM> 69, 95&ndash;106 (1997). The index should be good for
 data with high beta diversity and variable sampling
 intensity. Thanks to consultation to Yong Cao (Univ Illinois,
 USA).
@@ -1129,7 +1140,7 @@
 <ul>
 <li> <p><code>clamtest</code>: new function to classify species as
 generalists and specialists in two distinct habitats (CLAM test of
-Chazdon et al., <em>Ecology</em> 92, 1332&ndash;1343; 2011).  The test is
+Chazdon et al., <EM>Ecology</EM> 92, 1332&ndash;1343; 2011).  The test is
 based on multinomial distribution of individuals in two habitat
 types or sampling units, and it is applicable only to count data
 with no over-dispersion.
@@ -1149,7 +1160,7 @@
 <code>vegdist</code>, but that uses equal sampling probabilities for
 species and analytic equations. The new <code>raupcrick</code>
 function uses simulation with <code>oecosimu</code>. The function
-follows Chase et al. (2011) <em>Ecosphere</em> 2:art24
+follows Chase et al. (2011) <EM>Ecosphere</EM> 2:art24
 [<a href="http://www.esajournals.org/doi/abs/10.1890/ES10-00117.1">doi:10.1890/ES10-00117.1</a>],
 and was developed with the consultation of Brian Inouye.
 </p>
@@ -1182,12 +1193,12 @@
 <code>update</code>d because of a &lsquo;<span class="file">NAMESPACE</span>&rsquo; issue.
 </p>
 </li>
-<li> <p><span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> 2.14.0 changed so that it does not accept using
+<li> <p><font face="Courier New,Courier" color="#666666"><b>R</b></font> 2.14.0 changed so that it does not accept using
 <code>sd()</code> function for matrices (which was the behaviour at
-least since <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> 1.0-0), and several <span class="pkg">vegan</span> functions were
+least since <font face="Courier New,Courier" color="#666666"><b>R</b></font> 1.0-0), and several <span class="pkg">vegan</span> functions were
 changed to adapt to this change (<code>rda</code>, <code>capscale</code>,
 <code>simulate</code> methods for <code>rda</code>, <code>cca</code> and
-<code>capscale</code>). The change in <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> 2.14.0 does not influence the
+<code>capscale</code>). The change in <font face="Courier New,Courier" color="#666666"><b>R</b></font> 2.14.0 does not influence the
 results but you probably wish to upgrade <span class="pkg">vegan</span> to avoid
 annoying warnings.
 </p>
@@ -1221,11 +1232,11 @@
 <li><p> Peter Minchin joins the <span class="pkg">vegan</span> team.
 </p>
 </li>
-<li> <p><span class="pkg">vegan</span> implements standard <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> &lsquo;<span class="file">NAMESPACE</span>&rsquo;. In
+<li> <p><span class="pkg">vegan</span> implements standard <font face="Courier New,Courier" color="#666666"><b>R</b></font> &lsquo;<span class="file">NAMESPACE</span>&rsquo;. In
 general, <code>S3</code> methods are not exported which means that you
 cannot directly use or see contents of functions like
 <code>cca.default</code>, <code>plot.cca</code> or <code>anova.ccabyterm</code>. To
-use these functions you should rely on <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span> delegation and simply
+use these functions you should rely on <font face="Courier New,Courier" color="#666666"><b>R</b></font> delegation and simply
 use <code>cca</code> and for its result objects use <code>plot</code> and
 <code>anova</code> without suffix <code>.cca</code>. To see the contents of
 the function you can use <code>:::</code>, such as
@@ -1272,7 +1283,7 @@
 <li> <p><code>eventstar</code> finds the minimum of the evenness profile
 on the Tsallis entropy, and uses this to find the corresponding
 values of diversity, evenness and numbers equivalent following
-Mendes et al. (<em>Ecography</em> 31, 450-456; 2008). The code was
+Mendes et al. (<EM>Ecography</EM> 31, 450-456; 2008). The code was
 contributed by Eduardo Ribeira Cunha and Heloisa Beatriz Antoniazi
 Evangelista and adapted to <span class="pkg">vegan</span> by Peter Solymos.
 </p>
@@ -1281,9 +1292,9 @@
 the species accumulation results from <code>specaccum</code>. The
 function can use new self-starting species accumulation models
 in <span class="pkg">vegan</span> or other self-starting non-linear regression
-models in <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>. The function can fit Arrhenius, Gleason, Gitay,
+models in <font face="Courier New,Courier" color="#666666"><b>R</b></font>. The function can fit Arrhenius, Gleason, Gitay,
 Lomolino (in <span class="pkg">vegan</span>), asymptotic, Gompertz,
-Michaelis-Menten, logistic and Weibull (in base <span style="font-family: Courier New, Courier; color: #666666;"><b>R</b></span>) models. The
+Michaelis-Menten, logistic and Weibull (in base <font face="Courier New,Courier" color="#666666"><b>R</b></font>) models. The
 function has <code>plot</code> and <code>predict</code> methods.
 </p>
 </li>
@@ -1292,7 +1303,7 @@
 <code>SSlomolino</code>. These can be used with <code>fitspecaccum</code> or
 directly in non-linear regression with <code>nls</code>. These functions
 were implemented because they were found good for species-area
-models by Dengler (<em>J. Biogeogr.</em> 36, 728-744; 2009).
+models by Dengler (<EM>J. Biogeogr.</EM> 36, 728-744; 2009).
 </p>
 </li></ul>
 


From noreply at r-forge.r-project.org  Fri Dec 12 14:47:02 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Fri, 12 Dec 2014 14:47:02 +0100 (CET)
Subject: [Vegan-commits] r2921 - pkg/vegan/vignettes
Message-ID: <20141212134702.69658186766@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-12 14:47:02 +0100 (Fri, 12 Dec 2014)
New Revision: 2921

Modified:
   pkg/vegan/vignettes/diversity-vegan.Rnw
   pkg/vegan/vignettes/vegan.bib
Log:
Conflicts:
	vignettes/diversity-vegan.Rnw

Modified: pkg/vegan/vignettes/diversity-vegan.Rnw
===================================================================
--- pkg/vegan/vignettes/diversity-vegan.Rnw	2014-12-12 09:01:27 UTC (rev 2920)
+++ pkg/vegan/vignettes/diversity-vegan.Rnw	2014-12-12 13:47:02 UTC (rev 2921)
@@ -67,7 +67,7 @@
 \begin{align}
 H &= - \sum_{i=1}^S p_i \log_b  p_i & \text{Shannon--Weaver}\\
 D_1 &= 1 - \sum_{i=1}^S p_i^2  &\text{Simpson}\\
-D_2 &= \frac{1}{\sum_{i=1}^S p_i^2}  &\text{inverse Simpson}
+D_2 &= \frac{1}{\sum_{i=1}^S p_i^2}  &\text{inverse Simpson}\,,
 \end{align}
 where $p_i$ is the proportion of species $i$, and $S$ is the number of
 species so that $\sum_{i=1}^S p_i = 1$, and $b$ is the base of the
@@ -92,9 +92,9 @@
 \pkg{vegan} also can estimate series of R\'{e}nyi and Tsallis
 diversities. R{\'e}nyi diversity of order $a$ is \citep{Hill73number}:
 \begin{equation}
-H_a = \frac{1}{1-a} \log \sum_{i=1}^S p_i^a
+H_a = \frac{1}{1-a} \log \sum_{i=1}^S p_i^a \,,
 \end{equation}
-or the corresponding Hill numbers $N_a = \exp(H_a)$.  Many common
+and the corresponding Hill number is $N_a = \exp(H_a)$.  Many common
 diversity indices are special cases of Hill numbers: $N_0 = S$, $N_1 =
 \exp(H')$, $N_2 = D_2$, and $N_\infty = 1/(\max p_i)$. The
 corresponding R\'{e}nyi diversities are $H_0 = \log(S)$, $H_1 = H'$, $H_2 =
@@ -117,7 +117,7 @@
 We can really regard a site more diverse if all of its R\'{e}nyi
 diversities are higher than in another site.  We can inspect this
 graphically using the standard \code{plot} function for the
-\code{renyi} result (Fig. \ref{fig:renyi}).
+\code{renyi} result (Fig.~\ref{fig:renyi}).
 \begin{figure}
 <<fig=true,echo=false>>=
 print(plot(R))
@@ -142,28 +142,28 @@
 solve this problem, we may try to rarefy species richness to the same
 number of individuals.  Expected number of species in a community
 rarefied from $N$ to $n$ individuals is \citep{Hurlbert71}:
-\begin{multline}
+\begin{equation}
 \label{eq:rare}
-\hat S_n = \sum_{i=1}^S (1 - q_i),\\ \text{where} \quad q_i = {N-x_i
-  \choose n} \Bigm /{N \choose n}
-\end{multline}
-where $x_i$ is the count of species $i$, and ${N \choose n}$ is the
+\hat S_n = \sum_{i=1}^S (1 - q_i)\,, \quad\text{where }  q_i =
+\frac{{N-x_i \choose n}}{{N \choose n}} \,.
+\end{equation}
+Here $x_i$ is the count of species $i$, and ${N \choose n}$ is the
 binomial coefficient, or the number of ways we can choose $n$ from
 $N$, and $q_i$ give the probabilities that species $i$ does \emph{not} occur in a
-sample of size $n$.  This is defined only when $N-x_i > n$, but for
+sample of size $n$.  This is positive only when $N-x_i \ge n$, but for
 other cases $q_i = 0$ or the species is sure to occur in the sample.
 The variance of rarefied richness is \citep{HeckEtal75}:
 \begin{multline}
 \label{eq:rarevar}
-s^2 = q_i (1-q_i)  \\ + 2 \sum_{i=1}^S \sum_{j>i} \left[ {N- x_i - x_j
-    \choose n} \Bigm / {N
-    \choose n} - q_i q_j\right]
+s^2 = q_i (1-q_i)  \\ + 2 \sum_{i=1}^S \sum_{j>i} \left[ \frac{{N- x_i - x_j
+    \choose n}}{ {N
+    \choose n}} - q_i q_j\right] \,.
 \end{multline}
-Equation \ref{eq:rarevar} actually is of the same form as the variance
+Equation~\ref{eq:rarevar} actually is of the same form as the variance
 of sum of correlated variables:
 \begin{equation}
 \VAR \left(\sum x_i \right) = \sum \VAR (x_i) + 2 \sum_{i=1}^S
-\sum_{j>i} \COV (x_i, x_j)
+\sum_{j>i} \COV (x_i, x_j) \,.
 \end{equation}
 
 The number of stems per hectare varies in our
@@ -215,7 +215,8 @@
 taxonomic distinctness $\Delta^*$ \citep{ClarkeWarwick98}:
 \begin{align}
   \Delta &= \frac{\sum \sum_{i<j} \omega_{ij} x_i x_j}{n (n-1) / 2}\\
-\Delta^* &= \frac{\sum \sum_{i<j} \omega_{ij} x_i x_j}{\sum \sum_{i<j} x_i x_j}
+\Delta^* &= \frac{\sum \sum_{i<j} \omega_{ij} x_i x_j}{\sum \sum_{i<j}
+  x_i x_j} \,.
 \end{align}
 These equations give the index values for a single site, and summation
 goes over species $i$ and $j$, and $\omega$ are the taxonomic
@@ -230,7 +231,8 @@
 to give $s \Delta^+$, or it can be used to estimate an index of
 variation in taxonomic distinctness $\Lambda^+$ \citep{ClarkeWarwick01}:
 \begin{equation}
-  \Lambda^+ = \frac{\sum \sum_{i<j} \omega_{ij}^2}{n (n-1) / 2} - (\Delta^+)^2
+  \Lambda^+ = \frac{\sum \sum_{i<j} \omega_{ij}^2}{n (n-1) / 2} -
+  (\Delta^+)^2 \,.
 \end{equation}
 
 We still need the taxonomic differences among species ($\omega$) to
@@ -254,7 +256,7 @@
   but taxonomic differences proved to be of little use in the Barro
   Colorado data: they only singled out sites with Monocots (palm
   trees) in the data.}
-but there is such a table for the Dune meadow data (Fig. \ref{fig:taxondive}):
+but there is such a table for the Dune meadow data (Fig.~\ref{fig:taxondive}):
 <<>>=
 data(dune)
 data(dune.taxon)
@@ -307,12 +309,12 @@
 In Fisher's log-series, the expected number of species $\hat f$ with $n$
 individuals is \citep{FisherEtal43}:
 \begin{equation}
-\hat f_n = \frac{\alpha x^n}{n}
+\hat f_n = \frac{\alpha x^n}{n} \,,
 \end{equation}
 where $\alpha$ is the diversity parameter, and $x$ is a nuisance
 parameter defined by $\alpha$ and total number
 of individuals $N$ in the site, $x = N/(N-\alpha)$.  Fisher's
-log-series for a randomly selected plot is (Fig. \ref{fig:fisher}):
+log-series for a randomly selected plot is (Fig.~\ref{fig:fisher}):
 <<>>=
 k <- sample(nrow(BCI), 1)
 fish <- fisherfit(BCI[k,])
@@ -369,7 +371,7 @@
 \hat a_r &= N \hat p_1 r^\gamma &\text{Zipf}\\
 \hat a_r &= N c (r + \beta)^\gamma &\text{Zipf--Mandelbrot}
 \end{align}
-Where $\hat a_r$ is the expected abundance of species at rank $r$, $S$
+In all these, $\hat a_r$ is the expected abundance of species at rank $r$, $S$
 is the number of species, $N$ is the number of individuals, $\Phi$ is
 a standard normal function, $\hat p_1$ is the estimated proportion of
 the most abundant species, and $\alpha$, $\mu$, $\sigma$, $\gamma$,
@@ -379,7 +381,7 @@
 abundances $a_r$, but there is no reason for this, and \code{radfit}
 is able to work with the original abundance data.  We have count data,
 and the default Poisson error looks appropriate, and our example data
-set gives (Fig. \ref{fig:rad}):
+set gives (Fig.~\ref{fig:rad}):
 <<>>=
 rad <- radfit(BCI[k,])
 rad
@@ -426,30 +428,31 @@
 \citep{UglandEtal03}:
 \begin{multline}
 \label{eq:kindt}
-\hat S_n = \sum_{i=1}^S (1 - p_i), \, \\ \text{where} \quad  p_i = {N- f_i
-\choose n} \Bigm / {N \choose n}
+\hat S_n = \sum_{i=1}^S (1 - p_i), \,\quad \text{where }
+p_i = \frac{{N- f_i \choose n}}{{N \choose n}} \,,
 \end{multline}
-where $f_i$ is the frequency of species $i$.  Approximate variance
+and $f_i$ is the frequency of species $i$.  Approximate variance
 estimator is:
 \begin{multline}
 \label{eq:kindtvar}
 s^2 = p_i (1 - p_i)  \\ + 2 \sum_{i=1}^S \sum_{j>i} \left( r_{ij}
-  \sqrt{p_i(1-p_i)} \sqrt{p_j (1-p_j)}\right)
+  \sqrt{p_i(1-p_i)} \sqrt{p_j (1-p_j)}\right) \,,
 \end{multline}
 where $r_{ij}$ is the correlation coefficient between species $i$ and
-$j$.  Both of these are unpublished: eq. \ref{eq:kindt} was developed
-by Roeland Kindt, and eq. \ref{eq:kindtvar} by Jari Oksanen. The third
+$j$.  Both of these are unpublished: eq.~\ref{eq:kindt} was developed
+by Roeland Kindt, and eq.~\ref{eq:kindtvar} by Jari Oksanen. The third
 analytic method was suggested by \citet{Coleman82}:
 \begin{equation}
 \label{eq:cole}
-S_n = \sum_{i=1}^S (1 - p_i), \, \text{where} \quad p_i = \left(1 - \frac{1}{n}\right)^{f_i}
+S_n = \sum_{i=1}^S (1 - p_i), \quad \text{where }  p_i = \left(1 -
+  \frac{1}{n}\right)^{f_i} \,,
 \end{equation}
-and he suggested variance $s^2 = p_i (1-p_i)$ which ignores the
-covariance component.  In addition, eq. \ref{eq:cole} does not
+and the suggested variance is $s^2 = p_i (1-p_i)$ which ignores the
+covariance component.  In addition, eq.~\ref{eq:cole} does not
 properly handle sampling without replacement and underestimates the
 species accumulation curve.
 
-The recommended is Kindt's exact method (Fig. \ref{fig:sac}):
+The recommended is Kindt's exact method (Fig.~\ref{fig:sac}):
 <<a>>=
 sac <- specaccum(BCI)
 plot(sac, ci.type="polygon", ci.col="yellow")
@@ -478,7 +481,7 @@
 richness per one site $\bar \alpha$ \citep{Tuomisto10a}:
 \begin{equation}
   \label{eq:beta}
-  \beta = S/\bar \alpha - 1
+  \beta = S/\bar \alpha - 1 \,.
 \end{equation}
 Subtraction of one means that $\beta = 0$ when there are no excess
 species or no heterogeneity between sites. For this index, no specific
@@ -488,16 +491,16 @@
 ncol(BCI)/mean(specnumber(BCI)) - 1
 @
 
-The index of eq. \ref{eq:beta} is problematic because $S$ increases
+The index of eq.~\ref{eq:beta} is problematic because $S$ increases
 with the number of sites even when sites are all subsets of the same
 community.  \citet{Whittaker60} noticed this, and suggested the index
 to be found from pairwise comparison of sites. If the number of shared
 species in two sites is $a$, and the numbers of species unique to each
 site are $b$ and $c$, then $\bar \alpha = (2a + b + c)/2$ and $S =
-a+b+c$, and index \ref{eq:beta} can be expressed as:
+a+b+c$, and index~\ref{eq:beta} can be expressed as:
 \begin{equation}
   \label{eq:betabray}
-  \beta = \frac{a+b+c}{(2a+b+c)/2} - 1 = \frac{b+c}{2a+b+c}
+  \beta = \frac{a+b+c}{(2a+b+c)/2} - 1 = \frac{b+c}{2a+b+c} \,.
 \end{equation}
 This is the S{\o}rensen index of dissimilarity, and it can be found
 for all sites using \pkg{vegan} function \code{vegdist} with
@@ -508,7 +511,7 @@
 @
 
 There are many other definitions of beta diversity in addition to
-eq. \ref{eq:beta}.  All commonly used indices can be found using
+eq.~\ref{eq:beta}.  All commonly used indices can be found using
 \code{betadiver} \citep{KoleffEtal03}. The indices in \code{betadiver}
 can be referred to by subscript name, or index number:
 <<>>=
@@ -520,7 +523,7 @@
 on the Arrhenius species--area model
 \begin{equation}
   \label{eq:arrhenius}
-  \hat S = c X^z
+  \hat S = c X^z\,,
 \end{equation}
 where $X$ is the area (size) of the patch or site, and $c$ and $z$ are
 parameters. Parameter $c$ is uninteresting, but $z$ gives the
@@ -541,7 +544,7 @@
 with respect to classes or factors \citep{Anderson06, AndersonEtal06}.
 There is no such classification available for the Barro Colorado
 Island data, and the example studies beta diversities in the
-management classes of the dune meadows (Fig. \ref{fig:betadisper}):
+management classes of the dune meadows (Fig.~\ref{fig:betadisper}):
 <<>>=
 data(dune)
 data(dune.env)
@@ -596,7 +599,7 @@
 \label{eq:chao}
 \hat f_0 = \begin{cases} 
     \frac{f_1^2}{2 f_2} \frac{N-1}{N} &\text{if } f_2 > 0 \\
-\frac{f_1 (f_1 -1)}{2}  \frac{N-1}{N} & \text{if } f_2 = 0
+\frac{f_1 (f_1 -1)}{2}  \frac{N-1}{N} & \text{if } f_2 = 0 \,.
 \end{cases}
 \end{equation}
 The latter case for $f_2=0$ is known as the bias-corrected
@@ -607,11 +610,11 @@
 \citep{SmithVanBelle84}:
 \begin{align}
 \hat f_0 &=  f_1 \frac{N-1}{N}  \\ 
-\hat f_0 & =  f_1 \frac{2N-3}{N}  + f_2 \frac{(N-2)^2}{N(N-1)}
+\hat f_0 & =  f_1 \frac{2N-3}{N}  + f_2 \frac{(N-2)^2}{N(N-1)} \,.
 \end{align}
 The boostrap estimator is \citep{SmithVanBelle84}:
 \begin{equation}
-\hat f_0 =  \sum_{i=1}^{S_o} (1-p_i)^N
+\hat f_0 =  \sum_{i=1}^{S_o} (1-p_i)^N \,.
 \end{equation}
 The idea in jackknife seems to be that we missed about as many species
 as we saw only once, and the idea in bootstrap that if we repeat
@@ -625,7 +628,7 @@
 \begin{multline}
 \label{eq:var-chao-basic}
 \VAR(\hat f_0) = f_1 \left(A^2 \frac{G^3}{4} + A^2 G^2 + A \frac{G}{2} \right),\\
-\text{where}\; A = \frac{N-1}{N}\;\text{and}\; G = \frac{f_1}{f_2} 
+\text{where } A = \frac{N-1}{N}\;\text{and } G = \frac{f_1}{f_2} \,.
 \end{multline}
 %% The variance of bias-corrected Chao estimate can be approximated by
 %% replacing the terms of eq.~\ref{eq:var-chao-basic} with the
@@ -635,18 +638,20 @@
 %% s^2 = A \frac{f_1(f_1-1)}{2} + A^2 \frac{f_1(2 f_1+1)^2}{(f_2+1)^2}\\
 %%  + A^2 \frac{f_1^2 f_2 (f_1 -1)^2}{4 (f_2 + 1)^4}
 %% \end{multline}
-For the bias-corrected form of eq.~\ref{eq:chao}  (case $f_2 = 0$), the he variance is 
+For the bias-corrected form of eq.~\ref{eq:chao}  (case $f_2 = 0$), the variance is
 \citep[who omit small-sample correction in some terms]{ChiuEtal14}:
 \begin{multline}
 \label{eq:var-chao-bc0}
-\VAR(\hat f_0) = \frac{1}{4} A^2 f_1 (2f_1 -1)^2 + \frac{1}{2} A f_1 (f_1-1) - \frac{1}{4}A^2 \frac{f_1^4}{S_p}
+\VAR(\hat f_0) = \tfrac{1}{4} A^2 f_1 (2f_1 -1)^2 + \tfrac{1}{2} A f_1
+(f_1-1) \\- \tfrac{1}{4}A^2 \frac{f_1^4}{S_p} \,.
 \end{multline}
 
 The variance of the first-order jackknife is based on the number of
 ``singletons'' $r$ (species occurring only once in the data) in sample
 plots \citep{SmithVanBelle84}:
 \begin{equation}
-\VAR(\hat f_0) = \left(\sum_{i=1}^N r_i^2 - \frac{f_1}{N}\right) \frac{N-1}{N}
+\VAR(\hat f_0) = \left(\sum_{i=1}^N r_i^2 - \frac{f_1}{N}\right)
+\frac{N-1}{N} \,.
 \end{equation}
 Variance of the second-order jackknife is not evaluated in
 \code{specpool} (but contributions are welcome).
@@ -657,7 +662,7 @@
   j}^{S_o} \left[(Z_{ij}/N)^N - q_i q_j \right] \\
 \text{where } q_i = (1-p_i)^N \, ,
 \end{multline}
-where $Z_{ij}$ is the number of sites where both species are absent.
+and $Z_{ij}$ is the number of sites where both species are absent.
 
 The extrapolated richness values for the whole BCI data are:
 <<>>=
@@ -701,7 +706,7 @@
 \begin{multline}
   \label{eq:var-chao-bc}
  s^2 = \frac{a_1(a_1-1)}{2} + \frac{a_1(2 a_1+1)^2}{(a_2+1)^2}\\
-  + \frac{a_1^2 a_2 (a_1 -1)^2}{4 (a_2 + 1)^4}
+  + \frac{a_1^2 a_2 (a_1 -1)^2}{4 (a_2 + 1)^4} \,.
 \end{multline}
 However, \pkg{vegan} does not use this, but instead the following more
 exact form which was directly derived from eq.~\ref{eq:chao-bc}
@@ -721,7 +726,7 @@
 \frac{a_1}{C_\mathrm{ACE}} \gamma^2\, , \quad \text{where}\\
 C_\mathrm{ACE} &= 1 - \frac{a_1}{N_\mathrm{rare}}\\
 \gamma^2 &= \frac{S_\mathrm{rare}}{C_\mathrm{ACE}} \sum_{i=1}^{10} i
-(i-1) a_1 \frac{N_\mathrm{rare} - 1}{N_\mathrm{rare}}
+(i-1) a_1 \frac{N_\mathrm{rare} - 1}{N_\mathrm{rare}}\,.
 \end{split}
 \end{equation}
 Now $a_1$ takes the place of $f_1$ above, and means the number of
@@ -741,7 +746,7 @@
 estimate the pool size.  Log-normal model has a finite number of
 species which can be found integrating the log-normal:
 \begin{equation}
-S_p = S_\mu \sigma \sqrt{2 \pi}
+S_p = S_\mu \sigma \sqrt{2 \pi} \,,
 \end{equation}
 where $S_\mu$ is the modal height or the expected number of species at
 maximum (at $\mu$), and $\sigma$ is the width.  Function
@@ -771,12 +776,12 @@
 We may see how the estimated probability of occurrence and observed
 numbers of stems relate in one of the more familiar species. We study
 only one species, and to avoid circular reasoning we do not include
-the target species in the smoothing (Fig. \ref{fig:beals}):
+the target species in the smoothing (Fig.~\ref{fig:beals}):
 <<a>>=
 j <- which(colnames(BCI) == "Ceiba.pentandra")
 plot(beals(BCI, species=j, include=FALSE), BCI[,j], 
-     main="Ceiba pentandra", xlab="Probability of occurrence",
-     ylab="Occurrence")
+     ylab="Occurrence", main="Ceiba pentandra", 
+     xlab="Probability of occurrence")
 @
 \begin{figure}
 <<fig=true,echo=false>>=

Modified: pkg/vegan/vignettes/vegan.bib
===================================================================
--- pkg/vegan/vignettes/vegan.bib	2014-12-12 09:01:27 UTC (rev 2920)
+++ pkg/vegan/vignettes/vegan.bib	2014-12-12 13:47:02 UTC (rev 2921)
@@ -266,7 +266,7 @@
 }
 
 @Article{Tothmeresz95,
-  author = 	 {B. Tothmeresz},
+  author = 	 {B. T{\'o}thm{\'e}r{\'e}sz},
   title = 	 {Comparison of different methods for diversity ordering},
   journal = 	 {Journal of Vegetation Science},
   year = 	 1995,


From noreply at r-forge.r-project.org  Tue Dec 30 16:55:45 2014
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Tue, 30 Dec 2014 16:55:45 +0100 (CET)
Subject: [Vegan-commits] r2923 - www
Message-ID: <20141230155545.D18021873CF@r-forge.r-project.org>

Author: jarioksa
Date: 2014-12-30 16:55:45 +0100 (Tue, 30 Dec 2014)
New Revision: 2923

Modified:
   www/NEWS.html
Log:
NEWS

Modified: www/NEWS.html
===================================================================
--- www/NEWS.html	2014-12-16 14:01:20 UTC (rev 2922)
+++ www/NEWS.html	2014-12-30 15:55:45 UTC (rev 2923)
@@ -12,6 +12,18 @@
 
 
 
+<h4>GENERAL</h4>
+
+
+<ul>
+<li><p> This is a maintenance release to avoid warning messages
+caused by changes in CRAN repository.
+</p>
+</li></ul>
+
+
+
+
 <h4>INSTALLATION</h4>
 
 
@@ -22,9 +34,9 @@
 </p>
 </li></ul>
 
+ 
 
 
-
 <h4>BUG FIXES</h4>
 
 
@@ -50,6 +62,18 @@
 supplementary material</a>.
 </p>
 </li>
+<li><p> Diversity accumulation functions <code>specaccum</code>,
+<code>renyiaccum</code>, <code>tsallisaccum</code>, <code>poolaccum</code> and
+<code>estaccumR</code> use now <span class="pkg">permute</span> package for permutations
+of the order of sampling sites. Normally these functions only
+need simple random permutation of sites, but restricted
+permutation of the <span class="pkg">permute</span> package and user-supplied
+permutation matrices can be used.
+</p>
+</li>
+<li> <p><code>estaccumR</code> function can use parallel processing.
+</p>
+</li>
 <li> <p><code>linestack</code> accepts now expressions as labels. This
 allows using mathematical symbols and formula given as
 mathematical expressions.