FcnsByCatHypothTests: EnvStats Functions for Hypothesis Tests
In EnvStats: Package for Environmental Statistics, Including US EPA Guidance

FcnsByCatHypothTests

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.