FcnsByCatHypothTests {EnvStats}R Documentation

EnvStats Functions for Hypothesis Tests

Description

The EnvStats functions listed below are useful for performing hypothesis tests not already built into R. See Power and Sample Size Calculations for a list of functions you can use to perform power and sample size calculations based on various hypothesis tests.

Details

For goodness-of-fit tests, see Goodness-of-Fit Tests.

Function Name Description
chenTTest Chen's modified one-sided t-test for skewed
distributions.
kendallTrendTest Nonparametric test for monotonic trend
based on Kendall's tau statistic (and
optional confidence interval for slope).
kendallSeasonalTrendTest Nonparametric test for monotonic trend
within each season based on Kendall's tau
statistic (and optional confidence interval
for slope).
oneSamplePermutationTest Fisher's one-sample randomization
(permutation) test for location.
quantileTest Two-sample rank test to detect a shift in
a proportion of the “treated” population.
quantileTestPValue Compute p-value associated with a specified
combination of m, n, r and k
for the quantile test.
Useful for determining r and k for a
given significance level \alpha.
serialCorrelationTest Test for the presence of serial correlation.
signTest One- or paired-sample sign test on the
median.
twoSampleLinearRankTest Two-sample linear rank test to detect a
shift in the “treated” population.
twoSamplePermutationTestLocation Two-sample or paired-sample randomization
(permutation) test for location.
twoSamplePermutationTestProportion Randomization (permutation) test to compare
two proportions (Fisher's exact test).
varTest One-sample test on variance or two-sample
test to compare variances.
varGroupTest Test for homogeneity of variance among two
or more groups.
zTestGevdShape Estimate the shape parameter of a
Generalized Extreme Value distribution and
test the null hypothesis that the true
value is equal to 0.

[Package EnvStats version 2.8.1 Index]