The permustats
function extracts permutation results of
vegan functions. Its support functions can find quantiles and
standardized effect sizes, plot densities and QQ plots.
1 2 3 4 5 6 7 8 9 10 11  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", ...)

object, x, y 
The object to be handled. 
interval 
numeric; the coverage interval reported. 
xlab, ylab 
Arguments of

observed 
Add observed statistic among permutations. 
data 
Ignored. 
... 
Other arguments passed to the function. In

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 zvalues). It also prints the
the mean, median, and limits which contain interval
percent
of permuted values. With the default (interval = 0.95
), for
twosided test these are (2.5%, 97.5%) and for onesided 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 QQ 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
.
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.
Jari Oksanen with contributions from Gavin L. Simpson
(permustats.permutest.betadisper
method and related
modifications to summary.permustats
and the print
method) and Eduard SzĂ¶cs (permustats.anova.cca).
density
, densityplot
,
qqnorm
, qqmath
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  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)

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
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