rlm.test: Robust L1 Moment-Based (RLM) Goodness-of-Fit Test for the...

In gel-research-group/lawstat: Tools for Biostatistics, Public Policy, and Law

Description

Robust test for the Laplace distribution. Two options for calculating critical values, namely, approximated with Chi-square distribution and empirical, are available.

Usage

rlm.test(x, crit.values = c("chisq.approximation", "empirical"), N = 0)

Arguments

x	a numeric vector of data values.
crit.values	a character string specifying how the critical values should be obtained: approximated by the Chi-square distribution (default) or empirically.
N	number of Monte Carlo simulations for the empirical critical values.

Details

The test is based on a joint statistic using skewness and kurtosis coefficients. In particular, RLM uses the Average Absolute Deviation from the Median (MAAD), a robust estimate of standard deviation. See \insertCiteGel_2010;textuallawstat.

Value

A list of class "htest" with the following components:

statistic	the value of the test statistic.
parameter	the degrees of freedom.
p.value	the p-value of the test.
method	type of test was performed.
data.name	a character string giving the name of the data.

Author(s)

Kimihiro Noguchi, W. Wallace Hui, Yulia R. Gel

References

\insertAllCited

See Also

sj.test, rjb.test, rqq, jarque.bera.test

Examples

## Laplace distributed data
x = rexp(100) - rexp(100)
rlm.test(x)

gel-research-group/lawstat documentation built on Dec. 20, 2021, 9:50 a.m.