[Vegan-commits] r722 - in pkg/vegan: . man

[noreply at r-forge.r-project.org]

Author: psolymos
Date: 2009-03-07 18:30:11 +0100 (Sat, 07 Mar 2009)
New Revision: 722

Added:
   pkg/vegan/plot.permat.Rd
Removed:
   pkg/vegan/man/diagnose.permat.Rd
Log:
renaming Rd file


Deleted: pkg/vegan/man/diagnose.permat.Rd
===================================================================
--- pkg/vegan/man/diagnose.permat.Rd	2009-03-07 16:38:08 UTC (rev 721)
+++ pkg/vegan/man/diagnose.permat.Rd	2009-03-07 17:30:11 UTC (rev 722)
@@ -1,70 +0,0 @@
-\encoding{UTF-8}
-\name{diagnose.permat}
-\alias{plot.permat}
-\alias{lines.permat}
-\alias{lagplot.permat}
-\alias{lagplot}
-\alias{diagnose.permat}
-\alias{print.diagnose.permat}
-\alias{diagnose}
-
-\title{Diagnostic Tool for Matrix Permutation Algorithms}
-
-\description{ Plotting and diagnostic methods for 'permat' objects, that are useful in evaluating the performance of different null model settings, especially that of the sequential algorithms.}
-
-\usage{
-\method{plot}{permat}(x, type = "bray", ylab, xlab, col, lty,
-    lowess = TRUE, plot = TRUE, text = TRUE, ...)
-\method{lines}{permat}(x, type = "bray", ...)
-lagplot(x, ...)
-\method{lagplot}{permat}(x, type = "bray", ...)
-diagnose(x, ...)
-\method{diagnose}{permat}(x, type = "bray", ...)
-\method{print}{diagnose.permat}(x, ...)
-}
-\arguments{
-  \item{x}{Object of class \code{"permat"} created by the functions \code{\link{permatfull}} and \code{\link{permatswap}}.}
-  \item{ylab, xlab, col, lty}{graphical parameters for the \code{plot} method.}
-  \item{type}{Character, type of plot to be displayed: \code{"bray"} for Bray-Curtis dissimilarities, \code{"chisq"} for Chi-squared values.}
-  \item{lowess, plot, text}{Logical arguments for the \code{plot} method, whether a lowess curve should be drawn, the plot should be drawn, and statistic values should be printed on the plot.}
-  \item{\dots}{Other arguments passed to methods.}
-} 
-
-\details{
-
-The functions \code{lagplot} \code{diagnose} methods are useful for testing independence of permuted matrices
-when using sequential algorithms (\code{"swap", "tswap", "abuswap"}).
-
-}
-
-\value{
-The \code{diagnose} returns a list including first order autoregressive model and Ljung-Box test results to diagnose independence of the statistics (Bray-Curtis, Chi-square) derived from successive permuted matrices.
-}
-\author{\enc{P\'eter S\'olymos}{Peter Solymos}, \email{solymos at ualberta.ca} and Jari Oksanen}
-
-\seealso{
-For functions to create 'permat' objects: \code{\link{permatfull}}, \code{\link{permatswap}}
-
-For time-series diagnostics: \code{\link{Box.test}}, \code{\link{lag.plot}}, \code{\link{tsdiag}}
-}
-\examples{
-data(BCI)
-## Not sequential algorithm
-a <- permatswap(BCI, "quasiswap")
-## Sequential algorithm
-b <- permatswap(BCI, "abuswap", fixedmar="col",
-burnin=0, thin=100, times=50)
-opar <- par(mfrow=c(2,2))
-plot(a, main="Not sequential")
-plot(b, main="Sequential")
-plot(a, "chisq")
-plot(b, "chisq")
-par(opar)
-## The lagplot is useful to diagnose independence
-## of successive simulations for sequential algorithms
-lagplot.permat(b) # highly non-independent
-## Time series diagnostics
-diagnose(b)
-}
-
-\keyword{multivariate}

Copied: pkg/vegan/plot.permat.Rd (from rev 720, pkg/vegan/man/diagnose.permat.Rd)
===================================================================
--- pkg/vegan/plot.permat.Rd	                        (rev 0)
+++ pkg/vegan/plot.permat.Rd	2009-03-07 17:30:11 UTC (rev 722)
@@ -0,0 +1,70 @@
+\encoding{UTF-8}
+\name{diagnose.permat}
+\alias{plot.permat}
+\alias{lines.permat}
+\alias{lagplot.permat}
+\alias{lagplot}
+\alias{diagnose.permat}
+\alias{print.diagnose.permat}
+\alias{diagnose}
+
+\title{Diagnostic Tool for Matrix Permutation Algorithms}
+
+\description{ Plotting and diagnostic methods for 'permat' objects, that are useful in evaluating the performance of different null model settings, especially that of the sequential algorithms.}
+
+\usage{
+\method{plot}{permat}(x, type = "bray", ylab, xlab, col, lty,
+    lowess = TRUE, plot = TRUE, text = TRUE, ...)
+\method{lines}{permat}(x, type = "bray", ...)
+lagplot(x, ...)
+\method{lagplot}{permat}(x, type = "bray", ...)
+diagnose(x, ...)
+\method{diagnose}{permat}(x, type = "bray", ...)
+\method{print}{diagnose.permat}(x, ...)
+}
+\arguments{
+  \item{x}{Object of class \code{"permat"} created by the functions \code{\link{permatfull}} and \code{\link{permatswap}}.}
+  \item{ylab, xlab, col, lty}{graphical parameters for the \code{plot} method.}
+  \item{type}{Character, type of plot to be displayed: \code{"bray"} for Bray-Curtis dissimilarities, \code{"chisq"} for Chi-squared values.}
+  \item{lowess, plot, text}{Logical arguments for the \code{plot} method, whether a lowess curve should be drawn, the plot should be drawn, and statistic values should be printed on the plot.}
+  \item{\dots}{Other arguments passed to methods.}
+} 
+
+\details{
+
+The functions \code{lagplot} \code{diagnose} methods are useful for testing independence of permuted matrices
+when using sequential algorithms (\code{"swap", "tswap", "abuswap"}).
+
+}
+
+\value{
+The \code{diagnose} returns a list including first order autoregressive model and Ljung-Box test results to diagnose independence of the statistics (Bray-Curtis, Chi-square) derived from successive permuted matrices.
+}
+\author{\enc{P\'eter S\'olymos}{Peter Solymos}, \email{solymos at ualberta.ca} and Jari Oksanen}
+
+\seealso{
+For functions to create 'permat' objects: \code{\link{permatfull}}, \code{\link{permatswap}}
+
+For time-series diagnostics: \code{\link{Box.test}}, \code{\link{lag.plot}}, \code{\link{tsdiag}}
+}
+\examples{
+data(BCI)
+## Not sequential algorithm
+a <- permatswap(BCI, "quasiswap")
+## Sequential algorithm
+b <- permatswap(BCI, "abuswap", fixedmar="col",
+burnin=0, thin=100, times=50)
+opar <- par(mfrow=c(2,2))
+plot(a, main="Not sequential")
+plot(b, main="Sequential")
+plot(a, "chisq")
+plot(b, "chisq")
+par(opar)
+## The lagplot is useful to diagnose independence
+## of successive simulations for sequential algorithms
+lagplot.permat(b) # highly non-independent
+## Time series diagnostics
+diagnose(b)
+}
+
+\keyword{multivariate}