| randtest {ade4} | R Documentation |
randtest is a generic function. It proposes methods for the following objects between, discrimin, coinertia ...
randtest(xtest, ...)
## S3 method for class 'randtest'
plot(x, nclass = 10, coeff = 1, ...)
as.randtest (sim, obs,alter=c("greater", "less", "two-sided"), call = match.call())
## S3 method for class 'randtest'
print(x, ...)
xtest |
an object used to select a method |
x |
an object of class |
... |
|
nclass |
a number of intervals for the histogram |
coeff |
to fit the magnitude of the graph |
sim |
a numeric vector of simulated values |
obs |
a numeric vector of an observed value |
alter |
a character string specifying the alternative hypothesis, must be one of "greater" (default), "less" or "two-sided" |
call |
a call order |
If the alternative hypothesis is "greater", a p-value is estimated as: (number of random values equal to or greater than the observed one + 1)/(number of permutations + 1). The null hypothesis is rejected if the p-value is less than the significance level. If the alternative hypothesis is "less", a p-value is estimated as: (number of random values equal to or less than the observed one + 1)/(number of permutations + 1). Again, the null hypothesis is rejected if the p-value is less than the significance level. Lastly, if the alternative hypothesis is "two-sided", the estimation of the p-value is equivalent to the one used for "greater" except that random and observed values are firstly centered (using the average of random values) and secondly transformed to their absolute values. Note that this is only suitable for symmetric random distribution.
as.randtest returns a list of class randtest
plot.randtest draws the simulated values histograms and the position of the observed value
mantel.randtest, procuste.randtest, rtest
par(mfrow = c(2,2))
for (x0 in c(2.4,3.4,5.4,20.4)) {
l0 <- as.randtest(sim = rnorm(200), obs = x0)
print(l0)
plot(l0,main=paste("p.value = ", round(l0$pvalue, dig = 5)))
}
par(mfrow = c(1,1))