Extract, Analyse and Display Permutation Results

Description

The permustats function extracts permutation results of vegan functions. Its support functions can find quantiles and standardized effect sizes, plot densities and Q-Q plots.

Usage

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permustats(x, ...)
## S3 method for class 'permustats'
summary(object, interval = 0.95, ...)
## S3 method for class 'permustats'
densityplot(x, data, xlab = "Permutations", ...)
## S3 method for class 'permustats'
density(x, observed = TRUE, ...)
## S3 method for class 'permustats'
qqnorm(y, observed = TRUE, ...)
## S3 method for class 'permustats'
qqmath(x, data, observed = TRUE, ylab = "Permutations", ...)

Arguments

object, x, y

The object to be handled.

interval

numeric; the coverage interval reported.

xlab, ylab

Arguments of densityplot and qqmath functions.

observed

Add observed statistic among permutations.

data

Ignored.

...

Other arguments passed to the function. In density these are passed to density.default.

Details

The permustats function extracts permutation results and observed statistics from several vegan functions that perform permutations or simulations.

The summary method of permustats estimates the standardized effect sizes (SES) as the difference of observed statistic and mean of permutations divided by the standard deviation of permutations (also known as z-values). It also prints the the mean, median, and limits which contain interval percent of permuted values. With the default (interval = 0.95), for two-sided test these are (2.5%, 97.5%) and for one-sided tests either 5% or 95% quantile depending on the test direction. The mean, quantiles and z values are evaluated from permuted values without observed statistic.

The density and densityplot methods display the kernel density estimates of permuted values. When observed value of the statistic is included in the permuted values, the densityplot method marks the observed statistic as a vertical line. However the density method uses its standard plot method and cannot mark the obseved value.

The qqnorm and qqmath display Q-Q plots of permutations, optionally together with the observed value (default) which is shown as horizontal line in plots. qqnorm plots permutation values against standard Normal variate. qqmath defaults to the standard Normal as well, but can accept other alternatives (see standard qqmath).

Functions density and qqnorm are based on standard R methods and accept their arguments. They only handle one statistic, and cannot be used when several test statistic were evaluated. The densityplot and qqmath are lattice graphics, and can be used both for one and several statistics. All these functions pass arguments to their underlying functions; see their documentation.

The permustats can extract permutation statistics from the results of adonis, anosim, anova.cca, mantel, mantel.partial, mrpp, oecosimu, ordiareatest, permutest.cca, protest, and permutest.betadisper.

Value

The permustats function returns an object of class "permustats". This is a list of items "statistic" for observed statistics, permutations which contains permuted values, and alternative which contains text defining the character of the test ("two.sided", "less" or "greater"). The qqnorm and density methods return their standard result objects.

Author(s)

Jari Oksanen with contributions from Gavin L. Simpson (permustats.permutest.betadisper method and related modifications to summary.permustats and the print method) and Eduard Szöcs (permustats.anova.cca).

See Also

density, densityplot, qqnorm, qqmath.

Examples

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data(dune)
data(dune.env)
mod <- adonis(dune ~ Management + A1, data = dune.env)
## use permustats
perm <- permustats(mod)
summary(perm)
densityplot(perm)
qqmath(perm)

## example of multiple types of statistic
mod <- with(dune.env, betadisper(vegdist(dune), Management))
pmod <- permutest(mod, nperm = 99, pairwise = TRUE)
perm <- permustats(pmod)
summary(perm, interval = 0.90)

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