permustats
function extracts permutation results of
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", ...)
densityplot
and
qqmath
functions.density
these are passed to density.default
.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.permustats
function extracts permutation results and
observed statistics from several 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 Rmethods and accept their arguments. They only handle one
statistic, and cannot be used when several test statistic were
evaluated. The densityplot
and
qqmath
are
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
.
density
, densityplot
,
qqnorm
, qqmath
.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)
Run the code above in your browser using DataLab