h0plot: Visualize Distribution of Test Statistic.

In MKinfer: Inferential Statistics

Visualize Distribution of Test Statistic.

Description

The function visualizes the distribution of the test statistic.

Usage

h0plot(x, ...)

## Default S3 method:
h0plot(x, statistic, pval, alternative = "two.sided", sig.level = 0.05, 
                           hist.alpha = 0.2, stat.col = "darkgreen", dens.col = "black",
                           dens.alpha = 0.5, cval.col = "darkred", lwd = 1, 
                           breaks = NULL, digits = 3, ...)

## S3 method for class 'htest'
h0plot(x, sig.level = 0.05, hist.alpha = 0.2, 
                         stat.col = "darkgreen", dens.col = "black",
                         dens.alpha = 0.5, cval.col = "darkred", lwd = 1, 
                         breaks = NULL, digits = 3, qtail = 1e-3, n = 501, ...)

## S3 method for class 'perm.htest'
h0plot(x, sig.level = 0.05, hist.alpha = 0.2, stat.col = "darkgreen", 
                              dens.col = "black", dens.alpha = 0.5, 
                              cval.col = "darkred", lwd = 1, breaks = NULL, 
                              digits = 3, ...)

## S3 method for class 'boot.htest'
h0plot(x, sig.level = 0.05, hist.alpha = 0.2, stat.col = "darkgreen", 
                              dens.col = "black", dens.alpha = 0.5, cval.col = "darkred", 
                              lwd = 1, breaks = NULL, digits = 3, ...)

Arguments

x	bootstrap/permuation results of the test statistic or result of class htest, perm.htest, or boot.htest.
statistic	test statistic of the test on the original data.
pval	p value of the test.
alternative	a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.
sig.level	significance level of the test.
hist.alpha	opacity used for geom_histogram.
stat.col	color used for line representing the (final) test statistic.
dens.col	color used for the density line.
dens.alpha	opacity used for geom_area to color the rejection region.
cval.col	color used for rejection region (area under the density beyond the critical value).
lwd	line width used for line representing the (final) test statistic as well ase for geom_density.
breaks	argument breaks of geom_histogram.
digits	number of significant digits used for p values.
qtail	tail quantile to determine plot limits of x-axis.
n	integer; the number of x values at which to evaluate.
...	further arguments that may be passed through.

Details

The function can be used to plot the distribution of the test statistic under H0.

In case of class htest the implementation so far covers t.test, oneway.test, and var.test. In principle, the function should work for all tests of class htest returning a t or F statistic.

Value

ggplot object

Author(s)

Matthias Kohl [e-mail]

References

B. Efron, R.J. Tibshirani. An Introduction to the Bootstrap. Chapman and Hall/CRC 1993.

A. Janssen (1997). Studentized permutation tests for non-i.i.d, hypotheses and the generalized Behrens-Fisher problem. Statistics and Probability Letters, 36, 9-21.

E. Chung, J.P. Romano (2013). Exact and asymptotically robust permutation tests. The Annals of Statistics, 41(2), 484-507.

Examples

## Welch t-Test
h0plot(t.test(extra ~ group, data = sleep))
h0plot(t.test(extra ~ group, data = sleep, alternative = "less"))

## Hsu t-Test
h0plot(hsu.t.test(extra ~ group, data = sleep))
h0plot(hsu.t.test(extra ~ group, data = sleep, alternative = "less"))

## Welch 1-Way ANOVA
h0plot(oneway.test(extra ~ group, data = sleep))

## F test to compare two variances 
h0plot(var.test(extra ~ group, data = sleep))

## Bootstrap based Welch t-Test
h0plot(boot.t.test(extra ~ group, data = sleep, bootStat = TRUE))
h0plot(boot.t.test(extra ~ group, data = sleep, bootStat = TRUE, 
                   alternative = "less"))

## Permutation based Welch t-Test
h0plot(perm.t.test(extra ~ group, data = sleep, permStat = TRUE))
h0plot(perm.t.test(extra ~ group, data = sleep, permStat = TRUE, 
                   alternative = "less"))

MKinfer documentation built on Dec. 15, 2025, 9:06 a.m.