[Vegan-commits] r2229 - in pkg/vegan: . R inst man tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed Jul 11 08:21:22 CEST 2012
Author: jarioksa
Date: 2012-07-11 08:21:22 +0200 (Wed, 11 Jul 2012)
New Revision: 2229
Removed:
pkg/vegan/R/print.adipart.R
pkg/vegan/R/print.hiersimu.R
pkg/vegan/R/print.multipart.R
Modified:
pkg/vegan/NAMESPACE
pkg/vegan/R/adipart.default.R
pkg/vegan/R/hiersimu.default.R
pkg/vegan/R/multipart.default.R
pkg/vegan/R/print.oecosimu.R
pkg/vegan/inst/ChangeLog
pkg/vegan/man/adipart.Rd
pkg/vegan/man/multipart.Rd
pkg/vegan/tests/Examples/vegan-Ex.Rout.save
Log:
Merge branch 'master' into r-forge-svn-local
Modified: pkg/vegan/NAMESPACE
===================================================================
--- pkg/vegan/NAMESPACE 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/NAMESPACE 2012-07-11 06:21:22 UTC (rev 2229)
@@ -275,7 +275,6 @@
# print: base
S3method(print, CCorA)
S3method(print, MOStest)
-S3method(print, adipart)
S3method(print, adonis)
S3method(print, anosim)
S3method(print, betadisper)
@@ -288,7 +287,6 @@
S3method(print, envfit)
S3method(print, factorfit)
S3method(print, fisherfit)
-S3method(print, hiersimu)
S3method(print, humpfit)
S3method(print, isomap)
S3method(print, mantel)
@@ -297,7 +295,6 @@
S3method(print, monoMDS)
S3method(print, mrpp)
S3method(print, mso)
-S3method(print, multipart)
S3method(print, nestedchecker)
S3method(print, nesteddisc)
S3method(print, nestedn0)
Modified: pkg/vegan/R/adipart.default.R
===================================================================
--- pkg/vegan/R/adipart.default.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/adipart.default.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -101,11 +101,11 @@
call <- match.call()
call[[1]] <- as.name("adipart")
attr(sim, "call") <- call
- attr(sim, "index") <- index
- attr(sim, "weights") <- weights
+ attr(sim$oecosimu$simulated, "index") <- index
+ attr(sim$oecosimu$simulated, "weights") <- weights
attr(sim, "n.levels") <- nlevs
attr(sim, "terms") <- tlab
attr(sim, "model") <- rhs
- class(sim) <- c("adipart", "list")
+ class(sim) <- c("adipart", class(sim))
sim
}
Modified: pkg/vegan/R/hiersimu.default.R
===================================================================
--- pkg/vegan/R/hiersimu.default.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/hiersimu.default.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -90,6 +90,6 @@
attr(sim, "n.levels") <- nlevs
attr(sim, "terms") <- tlab
attr(sim, "model") <- rhs
- class(sim) <- c("hiersimu", "list")
+ class(sim) <- c("hiersimu", class(sim))
sim
}
Modified: pkg/vegan/R/multipart.default.R
===================================================================
--- pkg/vegan/R/multipart.default.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/multipart.default.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -126,12 +126,12 @@
call <- match.call()
call[[1]] <- as.name("multipart")
attr(sim, "call") <- call
- attr(sim, "index") <- index
- attr(sim, "scales") <- scales
- attr(sim, "global") <- TRUE
+ attr(sim$oecosimu$simulated, "index") <- index
+ attr(sim$oecosimu$simulated, "scales") <- scales
+ attr(sim$oecosimu$simulated, "global") <- TRUE
attr(sim, "n.levels") <- nlevs
attr(sim, "terms") <- tlab
attr(sim, "model") <- rhs
- class(sim) <- c("multipart", "list")
+ class(sim) <- c("multipart", class(sim))
sim
}
Deleted: pkg/vegan/R/print.adipart.R
===================================================================
--- pkg/vegan/R/print.adipart.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/print.adipart.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -1,32 +0,0 @@
-print.adipart <-
-function(x, ...)
-{
- n <- if (is.null(x$oecosimu$simulated))
- 0 else ncol(x$oecosimu$simulated)
- if (n > 0)
- cat("adipart with", n, "simulations using method",
- dQuote(x$oecosimu$method), "\n")
- else
- cat("adipart ")
- att <- attributes(x)
- att$names <- att$call <- att$class <- att$n.levels <- att$terms <- att$model <- NULL
- cat("with", paste(names(att), att, collapse=", "))
-
- cat("\n\n")
- cl <- class(x)
- if (length(cl) > 1 && cl[2] != "list") {
- NextMethod("print", x)
- cat("\n")
- }
- if (!is.null(x$oecosimu$simulated)) {
- tmp <- x$oecosimu$simulated
- } else {
- tmp <- data.matrix(x$oecosimu$statistic)
- }
- qu <- apply(tmp, 1, quantile, probs=c(0.025, 0.5, 0.975))
- m <- cbind("statistic" = x$oecosimu$statistic,
- "z" = x$oecosimu$z, t(qu),
- "Pr(sim.)"=x$oecosimu$pval)
- printCoefmat(m, ...)
- invisible(x)
-}
Deleted: pkg/vegan/R/print.hiersimu.R
===================================================================
--- pkg/vegan/R/print.hiersimu.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/print.hiersimu.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -1,16 +0,0 @@
-print.hiersimu <-
-function (x, ...)
-{
- cat("hiersimu with", ncol(x$oecosimu$simulated), "simulations\n\n")
- cl <- class(x)
- if (length(cl) > 1 && cl[2] != "list") {
- NextMethod("print", x)
- cat("\n")
- }
- qu <- apply(x$oecosimu$simulated, 1, quantile, probs = c(0.025,
- 0.5, 0.975))
- m <- cbind(statistic = x$oecosimu$statistic, z = x$oecosimu$z,
- t(qu), `Pr(sim.)` = x$oecosimu$pval)
- printCoefmat(m, ...)
- invisible(x)
-}
Deleted: pkg/vegan/R/print.multipart.R
===================================================================
--- pkg/vegan/R/print.multipart.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/print.multipart.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -1,27 +0,0 @@
-print.multipart <-
-function(x, ...)
-{
- n <- if (is.null(x$oecosimu$simulated))
- 0 else ncol(x$oecosimu$simulated)
- cat("multipart with", n, "simulations\n")
- att <- attributes(x)
- att$names <- att$call <- att$class <- att$n.levels <- att$terms <- att$model <- NULL
- cat("with", paste(names(att), att, collapse=", "))
- cat("\n\n")
- cl <- class(x)
- if (length(cl) > 1 && cl[2] != "list") {
- NextMethod("print", x)
- cat("\n")
- }
- if (!is.null(x$oecosimu$simulated)) {
- tmp <- x$oecosimu$simulated
- } else {
- tmp <- data.matrix(x$oecosimu$statistic)
- }
- qu <- apply(tmp, 1, quantile, probs=c(0.025, 0.5, 0.975))
- m <- cbind("statistic" = x$oecosimu$statistic,
- "z" = x$oecosimu$z, t(qu),
- "Pr(sim.)"=x$oecosimu$pval)
- printCoefmat(m, ...)
- invisible(x)
-}
Modified: pkg/vegan/R/print.oecosimu.R
===================================================================
--- pkg/vegan/R/print.oecosimu.R 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/R/print.oecosimu.R 2012-07-11 06:21:22 UTC (rev 2229)
@@ -8,7 +8,7 @@
ncol(x$oecosimu$simulated), "simulations\n")
if (length(att <- attributes(x$oecosimu$simulated)) > 1) {
att$dim <- NULL
- cat(" with", paste(names(att), att, collapse=", "))
+ cat("options: ", paste(names(att), att, collapse=", "))
}
alt.char <- switch(x$oecosimu$alternative,
two.sided = "not equal to",
@@ -19,9 +19,10 @@
cat("\n\n")
cl <- class(x)
- if (length(cl) > 1 && cl[2] != "list") {
- NextMethod("print", x)
- cat("\n")
+ if ((length(cl) > 1 && cl[2] != "list" ) &&
+ !any(cl %in% c("adipart", "hiersimu", "multipart"))) {
+ NextMethod("print", x)
+ cat("\n")
}
probs <- switch(x$oecosimu$alternative,
two.sided = c(0.025, 0.5, 0.975),
Modified: pkg/vegan/inst/ChangeLog
===================================================================
--- pkg/vegan/inst/ChangeLog 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/inst/ChangeLog 2012-07-11 06:21:22 UTC (rev 2229)
@@ -16,8 +16,13 @@
the formula and calls the default method for the actual
calculations without replicating its code. The "call" attribute of
these functions now returns the generic function name without
- ".default", ".formula" suffix.
+ ".default", ".formula" suffix.
+ Functions use now print.oecosimu() for displaying results and
+ their specific print.*() functions were deleted. This involved
+ changes in attributes: the printed attributes are now in
+ object$oecosimu$simulated instead of object.
+
* oecosimu: returns "call" attribute similarly as adipart(),
hiersimu() and multipart(). The print.oecosimu() output changed,
and shows the call. print.oecosimu() is able to display adipart(),
Modified: pkg/vegan/man/adipart.Rd
===================================================================
--- pkg/vegan/man/adipart.Rd 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/man/adipart.Rd 2012-07-11 06:21:22 UTC (rev 2229)
@@ -3,11 +3,10 @@
\alias{adipart}
\alias{adipart.default}
\alias{adipart.formula}
-\alias{print.adipart}
\alias{hiersimu}
\alias{hiersimu.default}
\alias{hiersimu.formula}
-\alias{print.hiersimu}
+
\title{Additive Diversity Partitioning and Hierarchical Null Model Testing}
\description{
In additive diversity partitioning, mean values of alpha diversity at lower levels of a sampling
Modified: pkg/vegan/man/multipart.Rd
===================================================================
--- pkg/vegan/man/multipart.Rd 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/man/multipart.Rd 2012-07-11 06:21:22 UTC (rev 2229)
@@ -3,7 +3,6 @@
\alias{multipart}
\alias{multipart.default}
\alias{multipart.formula}
-\alias{print.multipart}
\title{Multiplicative Diversity Partitioning}
\description{
Modified: pkg/vegan/tests/Examples/vegan-Ex.Rout.save
===================================================================
--- pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2012-07-11 06:21:19 UTC (rev 2228)
+++ pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2012-07-11 06:21:22 UTC (rev 2229)
@@ -1,8 +1,8 @@
-R Under development (unstable) (2012-06-11 r59557) -- "Unsuffered Consequences"
+R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
-Platform: x86_64-unknown-linux-gnu (64-bit)
+Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
@@ -23,7 +23,7 @@
> options(warn = 1)
> library('vegan')
Loading required package: permute
-This is vegan 2.1-16
+This is vegan 2.1-17
>
> assign(".oldSearch", search(), pos = 'CheckExEnv')
> cleanEx()
@@ -154,14 +154,14 @@
> plot(ef)
> ordisurf(mod ~ pH, varechem, knots = 1, add = TRUE)
Loading required package: mgcv
-This is mgcv 1.7-17. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-18. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ poly(x1, 1) + poly(x2, 1)
-<environment: 0x2622380>
+<environment: 0x102410b90>
Total model degrees of freedom 3
GCV score: 0.0427924
@@ -491,8 +491,8 @@
> ### Name: adipart
> ### Title: Additive Diversity Partitioning and Hierarchical Null Model
> ### Testing
-> ### Aliases: adipart adipart.default adipart.formula print.adipart hiersimu
-> ### hiersimu.default hiersimu.formula print.hiersimu
+> ### Aliases: adipart adipart.default adipart.formula hiersimu
+> ### hiersimu.default hiersimu.formula
> ### Keywords: multivariate
>
> ### ** Examples
@@ -523,58 +523,79 @@
> par(mfrow=c(1,1))
> ## Additive diversity partitioning
> adipart(mite, index="richness", nsimul=19)
-adipart with 19 simulations using method “r2dtable”
-with index richness, weights unif
+Call: adipart(y = mite, index = "richness", nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-alpha.1 15.114 -38.430 22.032 22.300 22.608 0.05 *
-gamma 35.000 0.000 35.000 35.000 35.000 1.00
-beta.1 19.886 38.430 12.392 12.700 12.968 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+options: index richness, weights unif
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+alpha.1 15.114 -38.43 22.344 22.032 22.300 22.608 0.05 *
+gamma 35.000 0.00 35.000 35.000 35.000 35.000 1.00
+beta.1 19.886 38.43 12.656 12.392 12.700 12.968 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> adipart(mite ~ ., levsm, index="richness", nsimul=19)
-adipart with 19 simulations using method “r2dtable”
-with index richness, weights unif
+Call: adipart(formula = mite ~ ., data = levsm, index = "richness",
+nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-alpha.1 15.1143 -46.2370 22.1257 22.4429 22.6236 0.05 *
-alpha.2 29.7500 -21.7076 34.3625 35.0000 35.0000 0.05 *
-alpha.3 33.0000 0.0000 35.0000 35.0000 35.0000 0.05 *
-gamma 35.0000 0.0000 35.0000 35.0000 35.0000 1.00
-beta.1 14.6357 9.0407 12.0075 12.4286 12.8743 0.05 *
-beta.2 3.2500 13.1373 0.0000 0.0000 0.6375 0.05 *
-beta.3 2.0000 0.0000 0.0000 0.0000 0.0000 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+options: index richness, weights unif
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+alpha.1 15.114 -46.2370 22.39624 22.12571 22.44286 22.6236 0.05 *
+alpha.2 29.750 -21.7076 34.81579 34.36250 35.00000 35.0000 0.05 *
+alpha.3 33.000 0.0000 35.00000 35.00000 35.00000 35.0000 0.05 *
+gamma 35.000 0.0000 35.00000 35.00000 35.00000 35.0000 1.00
+beta.1 14.636 9.0407 12.41955 12.00750 12.42857 12.8743 0.05 *
+beta.2 3.250 13.1373 0.18421 0.00000 0.00000 0.6375 0.05 *
+beta.3 2.000 0.0000 0.00000 0.00000 0.00000 0.0000 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> ## Hierarchical null model testing
> ## diversity analysis (similar to adipart)
> hiersimu(mite, FUN=diversity, relative=TRUE, nsimul=19)
-hiersimu with 19 simulations
+Call: hiersimu(y = mite, FUN = diversity, relative = TRUE, nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-level_1 0.76064 -71.19509 0.93487 0.93856 0.9444 0.05 *
-leve_2 1.00000 0.00000 1.00000 1.00000 1.0000 1.00
+nullmodel method ‘r2dtable’ with 19 simulations
+
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+level_1 0.76064 -71.195 0.93904 0.93487 0.93856 0.9444 0.05 *
+leve_2 1.00000 0.000 1.00000 1.00000 1.00000 1.0000 1.00
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> hiersimu(mite ~., levsm, FUN=diversity, relative=TRUE, nsimul=19)
-hiersimu with 19 simulations
+Call: hiersimu(formula = mite ~ ., data = levsm, FUN = diversity,
+relative = TRUE, nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-l1 0.76064 -75.13855 0.93389 0.93819 0.9427 0.05 *
-l2 0.89736 -110.96786 0.99699 0.99814 0.9999 0.05 *
-l3 0.92791 -417.33833 0.99904 0.99943 0.9996 0.05 *
-l4 1.00000 0.00000 1.00000 1.00000 1.0000 1.00
+nullmodel method ‘r2dtable’ with 19 simulations
+
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+l1 0.76064 -75.139 0.93833 0.93389 0.93819 0.9427 0.05 *
+l2 0.89736 -110.968 0.99811 0.99699 0.99814 0.9999 0.05 *
+l3 0.92791 -417.338 0.99940 0.99904 0.99943 0.9996 0.05 *
+l4 1.00000 0.000 1.00000 1.00000 1.00000 1.0000 1.00
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> ## Hierarchical testing with the Morisita index
> morfun <- function(x) dispindmorisita(x)$imst
> hiersimu(mite ~., levsm, morfun, drop.highest=TRUE, nsimul=19)
-hiersimu with 19 simulations
+Call: hiersimu(formula = mite ~ ., data = levsm, FUN = morfun,
+drop.highest = TRUE, nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-l1 0.52070 8.52164 0.32262 0.35107 0.3848 0.05 *
-l2 0.60234 14.38537 0.09670 0.15043 0.1969 0.05 *
-l3 0.67509 20.31622 -0.23479 -0.19594 -0.0988 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+l1 0.52070 8.5216 0.353253 0.322624 0.351073 0.3848 0.05 *
+l2 0.60234 14.3854 0.153047 0.096700 0.150434 0.1969 0.05 *
+l3 0.67509 20.3162 -0.182473 -0.234793 -0.195937 -0.0988 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
@@ -2552,7 +2573,7 @@
Run 17 stress 0.1825664
... New best solution
... procrustes: rmse 0.0421789 max resid 0.1544029
-Run 18 stress 0.1843201
+Run 18 stress 0.1843199
Run 19 stress 0.2570123
Run 20 stress 0.3760596
> (fit <- envfit(ord, varechem, perm = 999))
@@ -3020,7 +3041,7 @@
Run 17 stress 0.1825664
... New best solution
... procrustes: rmse 0.0421789 max resid 0.1544029
-Run 18 stress 0.1843201
+Run 18 stress 0.1843199
Run 19 stress 0.2570123
Run 20 stress 0.3760596
> stressplot(mod)
@@ -3946,7 +3967,7 @@
>
> ### Name: multipart
> ### Title: Multiplicative Diversity Partitioning
-> ### Aliases: multipart multipart.default multipart.formula print.multipart
+> ### Aliases: multipart multipart.default multipart.formula
> ### Keywords: multivariate
>
> ### ** Examples
@@ -3971,59 +3992,75 @@
+ l4=cutter(mite.xy$y, cut = seq(0, 10, by = 10)))
> ## Multiplicative diversity partitioning
> multipart(mite, levsm, index="renyi", scales=1, nsimul=19)
-multipart with 19 simulations
-with index renyi, scales 1, global TRUE
+Call: multipart(y = mite, x = levsm, index = "renyi", scales = 1,
+nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-alpha.1 8.05548 -50.06937 12.06155 12.19041 12.3400 0.05 *
-alpha.2 11.23526 -91.66217 14.05255 14.08685 14.1485 0.05 *
-alpha.3 12.00644 -391.05300 14.13048 14.13932 14.1485 0.05 *
-gamma 14.16027 0.00000 14.16027 14.16027 14.1603 1.00
-beta.1 1.35678 27.32039 1.14474 1.15859 1.1683 0.05 *
-beta.2 1.07103 30.43075 0.99912 1.00340 1.0059 0.05 *
-beta.3 1.17939 460.54976 1.00083 1.00148 1.0021 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+options: index renyi, scales 1, global TRUE
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+alpha.1 8.0555 -50.069 12.19396 12.06155 12.19041 12.3400 0.05 *
+alpha.2 11.2353 -91.662 14.09161 14.05255 14.08685 14.1485 0.05 *
+alpha.3 12.0064 -391.053 14.13939 14.13048 14.13932 14.1485 0.05 *
+gamma 14.1603 0.000 14.16027 14.16027 14.16027 14.1603 1.00
+beta.1 1.3568 27.320 1.15770 1.14474 1.15859 1.1683 0.05 *
+beta.2 1.0710 30.431 1.00339 0.99912 1.00340 1.0059 0.05 *
+beta.3 1.1794 460.550 1.00148 1.00083 1.00148 1.0021 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> multipart(mite ~ ., levsm, index="renyi", scales=1, nsimul=19)
-multipart with 19 simulations
-with index renyi, scales 1, global TRUE
+Call: multipart(formula = mite ~ ., data = levsm, index = "renyi",
+scales = 1, nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-alpha.1 8.0555 -66.6425 12.1143 12.2120 12.2910 0.05 *
-alpha.2 11.2353 -94.6265 14.0246 14.0917 14.1193 0.05 *
-alpha.3 12.0064 -355.9621 14.1283 14.1374 14.1485 0.05 *
-gamma 14.1603 0.0000 14.1603 14.1603 14.1603 1.00
-beta.1 1.3568 35.0277 1.1478 1.1565 1.1660 0.05 *
-beta.2 1.0710 33.4227 1.0015 1.0035 1.0078 0.05 *
-beta.3 1.1794 419.1662 1.0008 1.0016 1.0023 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+options: index renyi, scales 1, global TRUE
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+alpha.1 8.0555 -66.643 12.2056 12.1143 12.2120 12.2910 0.05 *
+alpha.2 11.2353 -94.626 14.0818 14.0246 14.0917 14.1193 0.05 *
+alpha.3 12.0064 -355.962 14.1391 14.1283 14.1374 14.1485 0.05 *
+gamma 14.1603 0.000 14.1603 14.1603 14.1603 14.1603 1.00
+beta.1 1.3568 35.028 1.1566 1.1478 1.1565 1.1660 0.05 *
+beta.2 1.0710 33.423 1.0041 1.0015 1.0035 1.0078 0.05 *
+beta.3 1.1794 419.166 1.0015 1.0008 1.0016 1.0023 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> multipart(mite ~ ., levsm, index="renyi", scales=1, nsimul=19, relative=TRUE)
-multipart with 19 simulations
-with index renyi, scales 1, global TRUE
+Call: multipart(formula = mite ~ ., data = levsm, index = "renyi",
+scales = 1, relative = TRUE, nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-alpha.1 8.055481 -53.543897 12.071168 12.198307 12.3689 0.05 *
-alpha.2 11.235261 -99.506116 14.032767 14.076147 14.1247 0.05 *
-alpha.3 12.006443 -343.945577 14.123604 14.136297 14.1438 0.05 *
-gamma 14.160271 0.000000 14.160271 14.160271 14.1603 1.00
-beta.1 0.078594 19.567843 0.067236 0.068392 0.0691 0.05 *
-beta.2 0.535514 35.965825 0.500294 0.502062 0.5035 0.05 *
-beta.3 0.589695 404.814230 0.500583 0.500848 0.5013 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+options: index renyi, scales 1, global TRUE
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+alpha.1 8.055481 -53.544 12.204883 12.071168 12.198307 12.3689 0.05 *
+alpha.2 11.235261 -99.506 14.079276 14.032767 14.076147 14.1247 0.05 *
+alpha.3 12.006443 -343.946 14.135245 14.123604 14.136297 14.1438 0.05 *
+gamma 14.160271 0.000 14.160271 14.160271 14.160271 14.1603 1.00
+beta.1 0.078594 19.568 0.068267 0.067236 0.068392 0.0691 0.05 *
+beta.2 0.535514 35.966 0.501994 0.500294 0.502062 0.5035 0.05 *
+beta.3 0.589695 404.814 0.500885 0.500583 0.500848 0.5013 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> multipart(mite ~ ., levsm, index="renyi", scales=1, nsimul=19, global=TRUE)
-multipart with 19 simulations
-with index renyi, scales 1, global TRUE
+Call: multipart(formula = mite ~ ., data = levsm, index = "renyi",
+scales = 1, global = TRUE, nsimul = 19)
- statistic z 2.5% 50% 97.5% Pr(sim.)
-alpha.1 8.05548 -69.63045 12.09434 12.18504 12.3160 0.05 *
-alpha.2 11.23526 -81.67569 14.05248 14.09208 14.1625 0.05 *
-alpha.3 12.00644 -321.41937 14.12429 14.13991 14.1456 0.05 *
-gamma 14.16027 0.00000 14.16027 14.16027 14.1603 1.00
-beta.1 1.75784 105.55202 1.14975 1.16210 1.1708 0.05 *
-beta.2 1.26034 102.69533 0.99985 1.00484 1.0077 0.05 *
-beta.3 1.17939 378.33472 1.00104 1.00144 1.0025 0.05 *
+nullmodel method ‘r2dtable’ with 19 simulations
+options: index renyi, scales 1, global TRUE
+alternative hypothesis: simulated median is not equal to the statistic
+
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+alpha.1 8.0555 -69.630 12.19342 12.09434 12.18504 12.3160 0.05 *
+alpha.2 11.2353 -81.676 14.09224 14.05248 14.09208 14.1625 0.05 *
+alpha.3 12.0064 -321.419 14.13850 14.12429 14.13991 14.1456 0.05 *
+gamma 14.1603 0.000 14.16027 14.16027 14.16027 14.1603 1.00
+beta.1 1.7578 105.552 1.16133 1.14975 1.16210 1.1708 0.05 *
+beta.2 1.2603 102.695 1.00483 0.99985 1.00484 1.0077 0.05 *
+beta.3 1.1794 378.335 1.00154 1.00104 1.00144 1.0025 0.05 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
@@ -4056,8 +4093,11 @@
Checkerboard Units : 2767
C-score (species mean): 2.258776
> oecosimu(sipoo, nestedchecker, "quasiswap")
-oecosimu with 99 simulations
-simulation method ‘quasiswap’
+Call: oecosimu(comm = sipoo, nestfun = nestedchecker, method =
+"quasiswap")
+
+nullmodel method ‘quasiswap’ with 99 simulations
+
alternative hypothesis: simulated median is not equal to the statistic
Checkerboard Units : 2767
@@ -4067,8 +4107,11 @@
statistic 2767 0.84129 2698.1 2584.4 2676.0 2858.1 0.39
> ## Another Null model and standardized checkerboard score
> oecosimu(sipoo, nestedchecker, "r00", statistic = "C.score")
-oecosimu with 99 simulations
-simulation method ‘r00’
+Call: oecosimu(comm = sipoo, nestfun = nestedchecker, method = "r00",
+statistic = "C.score")
+
+nullmodel method ‘r00’ with 99 simulations
+
alternative hypothesis: simulated median is not equal to the statistic
Checkerboard Units : 2767
@@ -4191,8 +4234,10 @@
> data(sipoo)
> ## Traditional nestedness statistics (number of checkerboard units)
> oecosimu(sipoo, nestedchecker, "r0")
-oecosimu with 99 simulations
-simulation method ‘r0’
+Call: oecosimu(comm = sipoo, nestfun = nestedchecker, method = "r0")
+
+nullmodel method ‘r0’ with 99 simulations
+
alternative hypothesis: simulated median is not equal to the statistic
Checkerboard Units : 2767
@@ -4206,8 +4251,11 @@
> out <- oecosimu(sipoo, decorana, "swap", burnin=100, thin=10,
+ statistic="evals", alt = "less")
> out
-oecosimu with 99 simulations
-simulation method ‘swap’ with thin 10, burnin 100
+Call: oecosimu(comm = sipoo, nestfun = decorana, method = "swap",
+burnin = 100, thin = 10, statistic = "evals", alternative = "less")
+
+nullmodel method ‘swap’ with 99 simulations
+options: thin 10, burnin 100
alternative hypothesis: simulated median is less than the statistic
@@ -4244,8 +4292,10 @@
> meandist <- function(x) mean(vegdist(x, "bray"))
> mbc1 <- oecosimu(dune, meandist, "r2dtable")
> mbc1
-oecosimu with 99 simulations
-simulation method ‘r2dtable’
+Call: oecosimu(comm = dune, nestfun = meandist, method = "r2dtable")
+
+nullmodel method ‘r2dtable’ with 99 simulations
+
alternative hypothesis: simulated median is not equal to the statistic
statistic z mean 2.5% 50% 97.5% Pr(sim.)
@@ -4264,8 +4314,10 @@
> cf <- commsim("myshuffle", foo, isSeq = FALSE, binary = FALSE,
+ mode = "double")
> oecosimu(dune, meandist, cf)
-oecosimu with 99 simulations
-simulation method ‘myshuffle’
+Call: oecosimu(comm = dune, nestfun = meandist, method = cf)
+
+nullmodel method ‘myshuffle’ with 99 simulations
+
alternative hypothesis: simulated median is not equal to the statistic
statistic z mean 2.5% 50% 97.5% Pr(sim.)
@@ -4804,17 +4856,17 @@
> vare.mds <- monoMDS(vare.dist)
> with(varechem, ordisurf(vare.mds, Baresoil, bubble = 5))
Loading required package: mgcv
-This is mgcv 1.7-17. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-18. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x912fb60>
+<environment: 0x109e1d800>
Estimated degrees of freedom:
-6.4351 total = 7.43507
+6.4351 total = 7.435071
GCV score: 144.1236
>
@@ -4827,7 +4879,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x9a7e380>
+<environment: 0x108eafe40>
Estimated degrees of freedom:
6.1039 total = 7.103853
@@ -4839,13 +4891,13 @@
> ## Get fitted values
> calibrate(fit)
1 2 3 4 5 6 7
-22.0644615 6.0132250 3.6350484 4.1019743 9.0030990 5.9202602 8.6399182
+22.0644614 6.0132251 3.6350483 4.1019742 9.0030989 5.9202601 8.6399184
8 9 10 11 12 13 14
-11.0719302 0.6561783 35.2282116 10.4346331 7.2900019 5.5710617 24.6503109
+11.0719303 0.6561781 35.2282118 10.4346331 7.2900018 5.5710617 24.6503110
15 16 17 18 19 20 21
-18.8754520 29.7286540 5.6158934 9.5869715 3.2876268 2.7111723 10.7832857
+18.8754521 29.7286543 5.6158934 9.5869716 3.2876267 2.7111721 10.7832857
22 23 24
- 3.0020415 9.8128952 7.3656934
+ 3.0020413 9.8128952 7.3656932
>
> ## Plot method
> plot(fit, what = "contour")
@@ -4976,14 +5028,14 @@
> ## Map of PCNMs in the sample plot
> ordisurf(mite.xy, scores(pcnm1, choi=1), bubble = 4, main = "PCNM 1")
Loading required package: mgcv
-This is mgcv 1.7-17. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-18. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x978d1e0>
+<environment: 0x107d94b18>
Estimated degrees of freedom:
8.9275 total = 9.927492
@@ -4996,7 +5048,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x72ee4f8>
+<environment: 0x10a0ad580>
Estimated degrees of freedom:
7.7529 total = 8.75294
@@ -5009,7 +5061,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x97ecca8>
+<environment: 0x109de61b8>
Estimated degrees of freedom:
8.8962 total = 9.89616
@@ -5775,8 +5827,8 @@
[2,] 0.1169579 0.9931369
Translation of averages:
- [,1] [,2]
-[1,] 1.79048e-17 9.246476e-19
+ [,1] [,2]
+[1,] 3.893131e-18 -9.725997e-18
Scaling of target:
[1] 0.6736868
@@ -6950,8 +7002,11 @@
> ## Significance test using Null model communities.
> ## The current choice fixes only site totals.
> oecosimu(dune, treedive, "r0", tree = cl)
-oecosimu with 99 simulations
-simulation method ‘r0’
+Call: oecosimu(comm = dune, nestfun = treedive, method = "r0", tree =
+cl)
+
+nullmodel method ‘r0’ with 99 simulations
+
alternative hypothesis: simulated median is not equal to the statistic
statistic z mean 2.5% 50% 97.5% Pr(sim.)
@@ -7371,7 +7426,7 @@
Run 17 stress 0.1825664
... New best solution
... procrustes: rmse 0.0421789 max resid 0.1544029
-Run 18 stress 0.1843201
+Run 18 stress 0.1843199
Run 19 stress 0.2570123
Run 20 stress 0.3760596
> plot(ord, type = "t")
@@ -7541,14 +7596,14 @@
> ## add fitted surface of diversity to the model
> ordisurf(mod, diversity(dune), add = TRUE)
Loading required package: mgcv
-This is mgcv 1.7-17. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-18. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x9a81d78>
+<environment: 0x10a886eb0>
Estimated degrees of freedom:
2 total = 3
@@ -8028,7 +8083,7 @@
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed: 25.377 0.088 25.548 0 0
+Time elapsed: 78.943 1.479 80.482 0 0
> grDevices::dev.off()
null device
1
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