[Vegan-commits] r660 - in pkg/vegan: inst man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Thu Jan 15 09:33:14 CET 2009


Author: jarioksa
Date: 2009-01-15 09:33:14 +0100 (Thu, 15 Jan 2009)
New Revision: 660

Modified:
   pkg/vegan/inst/ChangeLog
   pkg/vegan/man/cascadeKM.Rd
   pkg/vegan/man/cca.object.Rd
   pkg/vegan/man/mso.Rd
   pkg/vegan/man/vegdist.Rd
Log:
Corrected problems in Rd files reported by stricter Rd parser v2 in R 2.9.0 unstable (2009-01-13 r47593)

Modified: pkg/vegan/inst/ChangeLog
===================================================================
--- pkg/vegan/inst/ChangeLog	2009-01-14 19:31:02 UTC (rev 659)
+++ pkg/vegan/inst/ChangeLog	2009-01-15 08:33:14 UTC (rev 660)
@@ -4,21 +4,29 @@
 
 Version 1.16-9 (opened Jan 7, 2009)
 
-    * permatswap: new algorithm "swsh" is added to keep row/column
-    incidences (but not sums) constant. The name refers to the two
-    steps: (1) binary *sw*aps are made then (2) individuals in
-    non-zero cells are *sh*uffled.
+	* Checked with R version 2.9.0 Under development (unstable) 
+	(2009-01-13 r47593) having experimental strict Rd parser, and
+	corrected the reported problems in Rd files so that vegan is R
+	2.9.0-ready. 
 
-    * permat methods: calculations of the Chi-squared statistic is
-    added to summary, and the type argument can be used in the plot
-    "bray" or "chisq" values.
+	* adonis: uses now canonical (hits+1)/(tries+1) for P-values
+	instead of hits/tries.
 
+	* permatswap: new algorithm "swsh" is added to keep row/column
+	incidences (but not sums) constant. The name refers to the two
+	steps: (1) binary *sw*aps are made then (2) individuals in
+	non-zero cells are *sh*uffled.
+
+	* permat methods: calculations of the Chi-squared statistic is
+	added to summary, and the type argument can be used in the plot
+	"bray" or "chisq" values.
+
 	* nestednodf: gained argument 'order = TRUE' allowing tests for
 	other orderings than using marginal frequencies (default)
 	following suggestion by Almeida-Neto et al. (2008).
 
 	* summary.cca:  cumulative "accounted for" statistics failed in
-	unconstrained models. 
+	unconstrained models.
 	
 Version 1.16-8 (closed Jan 7, 2009)
 

Modified: pkg/vegan/man/cascadeKM.Rd
===================================================================
--- pkg/vegan/man/cascadeKM.Rd	2009-01-14 19:31:02 UTC (rev 659)
+++ pkg/vegan/man/cascadeKM.Rd	2009-01-15 08:33:14 UTC (rev 660)
@@ -75,18 +75,18 @@
   literally when the groups are not equal in size. Type \code{"all"} to
   obtain  both indices. The indices are defined as: 
   \describe{
-    \item \bold{calinski}:
+    \item{calinski:}{
     \eqn{(SSB/(K-1))/(SSW/(n-K))}, where \eqn{n} is the
     number of data points and \eqn{K} is the number of clusters.
     \eqn{SSW} is the sum of squares within the clusters while
     \eqn{SSB} is the sum of squares among the clusters. This index
-    is simply an \eqn{F} (ANOVA) statistic.
+    is simply an \eqn{F} (ANOVA) statistic.}
  
-    \item \bold{ssi}:
+    \item{ssi:}{
     the \dQuote{Simple Structure Index} multiplicatively combines
     several elements which influence the interpretability of a
     partitioning solution. The best partition is indicated by the
-    highest SSI value.
+    highest SSI value.}
   }
 
   In a simulation study, Milligan and Cooper (1985) found

Modified: pkg/vegan/man/cca.object.Rd
===================================================================
--- pkg/vegan/man/cca.object.Rd	2009-01-14 19:31:02 UTC (rev 659)
+++ pkg/vegan/man/cca.object.Rd	2009-01-15 08:33:14 UTC (rev 660)
@@ -42,12 +42,13 @@
     component.
     Items \code{pCCA}, \code{CCA} and \code{CA} have similar
     structure, and contain following items:
+    \describe{
     \item{\code{alias}}{The names of the aliased constraints or conditions.
       Function \code{\link{alias.cca}} does not access this item
       directly, but it finds the aliased variables and their defining
       equations from the \code{QR} item.}
     \item{\code{biplot}}{Biplot scores of constraints.  Only in \code{CCA}.}
-    \item{centroids}{(Weighted) centroids of factor levels of
+    \item{\code{centroids}}{(Weighted) centroids of factor levels of
       constraints. Only in \code{CCA}. Missing if the ordination was not
     called with \code{formula}.}
     \item{\code{eig}}{Eigenvalues of axes. In \code{CCA} and \code{CA}.}
@@ -104,7 +105,7 @@
       after both \code{pCCA} and \code{CCA}. In \code{\link{cca}} the
       standardization is Chi-square, and in \code{\link{rda}} centring
       and optional scaling by species standard deviations using function
-      \code{\link{scale}}. }
+      \code{\link{scale}}.} }
   }
 }
   

Modified: pkg/vegan/man/mso.Rd
===================================================================
--- pkg/vegan/man/mso.Rd	2009-01-14 19:31:02 UTC (rev 659)
+++ pkg/vegan/man/mso.Rd	2009-01-15 08:33:14 UTC (rev 660)
@@ -59,8 +59,8 @@
 \value{
   The function \code{mso} returns an amended \code{cca} or \code{rda}
   object with the additional attributes \code{grain}, \code{H},
-  \code{H.test} and \code{vario}.  
-  \item{grain }{ The grain attribute defines the interval size of the
+  \code{H.test} and \code{vario}.
+  \item{grain}{The grain attribute defines the interval size of the
     distance classes .} 
   \item{H }{ H is an object of class 'dist' and contains the geographic
     distances between observations.} 
@@ -69,27 +69,30 @@
     which distance class (columns). } 
   \item{vario }{ The vario attribute is a data frame that contains some
     or all of the following components for the rda case (cca case in
-    brackets): 
-    \item{H }{ Distance class as multiples of grain.}
-    \item{Dist }{ Average distance of pairs of observations in distance class H.}
-    \item{n }{ Number of unique pairs of observations in distance class
-      H.} 
-    \item{All }{ Empirical (chi-square) variogram of total variance
-      (inertia).} 
-    \item{Sum }{ Sum of empirical (chi-square) variograms of explained
-      and residual variance (inertia).} 
-    \item{CA }{ Empirical (chi-square) variogram of residual variance
-      (inertia).} 
-    \item{CCA }{ Empirical (chi-square) variogram of explained variance
-      (inertia).} 
-    \item{pCCA }{ Empirical (chi-square) variogram of conditioned
-      variance (inertia).} 
-    \item{se }{ Standard error of the empirical (chi-square) variogram
-      of total variance (inertia).} 
-    \item{CA.signif }{P-value of permutation test for spatial
-      independence of residual variance (inertia).} 
+      brackets):
+    \describe{
+      \item{\code{H}}{Distance class as multiples of grain.}
+      \item{\code{Dist}}{ Average distance of pairs of observations in distance class H.}
+      \item{n }{ Number of unique pairs of observations in distance class
+	H.} 
+      \item{\code{All}}{ Empirical (chi-square) variogram of total variance
+	(inertia).} 
+      \item{\code{Sum}}{ Sum of empirical (chi-square) variograms of explained
+	and residual variance (inertia).} 
+      \item{\code{CA}}{ Empirical (chi-square) variogram of residual variance
+	(inertia).} 
+      \item{\code{CCA}}{ Empirical (chi-square) variogram of explained variance
+	(inertia).} 
+      \item{\code{pCCA}}{ Empirical (chi-square) variogram of conditioned
+	variance (inertia).} 
+      \item{\code{se}}{ Standard error of the empirical (chi-square) variogram
+	of total variance (inertia).} 
+      \item{\code{CA.signif}}{P-value of permutation test for spatial
+	independence of residual variance (inertia).} 
+    }
   }
 }
+  
 \references{ Wagner, H.H. 2004. Direct multi-scale ordination with
   canonical correspondence analysis. \emph{Ecology} 85: 342--351. } 
 \author{ The responsible author was Helene Wagner.} 

Modified: pkg/vegan/man/vegdist.Rd
===================================================================
--- pkg/vegan/man/vegdist.Rd	2009-01-14 19:31:02 UTC (rev 659)
+++ pkg/vegan/man/vegdist.Rd	2009-01-15 08:33:14 UTC (rev 660)
@@ -73,10 +73,10 @@
       min(x[ij],x[ik])/(sum x[ik]))}
     \cr
     \code{morisita}
-    \tab {\eqn{d_{jk} = \frac{2 \sum_i x_{ij} x_{ik}}{(\lambda_j +
+    \tab \eqn{d_{jk} = \frac{2 \sum_i x_{ij} x_{ik}}{(\lambda_j +
 	  \lambda_k) \sum_i x_{ij} \sum_i
 	  x_{ik}}}{d[jk] = 2*sum(x[ij]*x[ik])/((lambda[j]+lambda[k]) *
-	sum(x[ij])*sum(x[ik]))}  }
+	sum(x[ij])*sum(x[ik]))}  
     \cr
     \tab where \eqn{\lambda_j = \frac{\sum_i x_{ij} (x_{ij} - 1)}{\sum_i
       x_{ij} \sum_i (x_{ij} - 1)}}{lambda[j] =



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