WRS2: pbcor – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

pbcor

Robust correlation coefficients.

Description

The pbcor function computes the percentage bend correlation coefficient, wincor the Winsorized correlation, pball the percentage bend correlation matrix, winall the Winsorized correlation matrix.

Usage

pbcor(x, y = NULL, beta = 0.2, ci = FALSE, nboot = 500, alpha = 0.05)
pball(x, beta = 0.2)
wincor(x, y = NULL, tr = 0.2, ci = FALSE, nboot = 500, alpha = 0.05)
winall(x, tr = 0.2)

Arguments

`x`	a numeric vector, a matrix or a data frame.
`y`	a second numeric vector (for correlation functions).
`beta`	bending constant.
`tr`	amount of Winsorization.
`ci`	whether boostrap CI should be computed or not.
`nboot`	number of bootstrap samples for CI computation.
`alpha`	alpha level for CI computation.

Details

It tested is whether the correlation coefficient equals 0 (null hypothesis) or not. Missing values are deleted pairwise. The tests are sensitive to heteroscedasticity. The test statistic H in pball tests the hypothesis that all correlations are equal to zero.

Value

pbcor and wincor return an object of class "pbcor" containing:

`cor`	robust correlation coefficient
`test`	value of the test statistic
`p.value`	p-value
`n`	number of effective observations
`cor_ci`	bootstrap confidence interval
`call`	function call

pball and winall return an object of class "pball" containing:

`pbcorm`	robust correlation matrix
`p.values`	p-values
`H`	H-statistic
`H.p.value`	p-value H-statistic
`cov`	variance-covariance matrix

References

Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.

Examples

x1 <- subset(hangover, subset = (group == "control" & time == 1))$symptoms
x2 <- subset(hangover, subset = (group == "control" & time == 2))$symptoms

pbcor(x1, x2)
pbcor(x1, x2, beta = 0.1, ci = TRUE)

wincor(x1, x2)
wincor(x1, x2, tr = 0.1, ci = TRUE)

require(reshape)
hanglong <- subset(hangover, subset = group == "control")
hangwide <- cast(hanglong, id ~ time, value = "symptoms")[,-1]

pball(hangwide)
winall(hangwide)

WRS2

A Collection of Robust Statistical Methods

v1.1-1

GPL-3

Authors

Patrick Mair [cre, aut], Rand Wilcox [aut]

Initial release

2021-02-09