pbcor: Robust correlation coefficients.

Description Usage Arguments Details Value References See Also Examples

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

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pbcor(x, y = NULL, beta = 0.2)
pball(x, beta = 0.2)
wincor(x, y = NULL, tr = 0.2)
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.

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

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.

See Also

twocor

Examples

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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)

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

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

pball(hangwide)
winall(hangwide)

Example output

Call:
pbcor(x = x1, y = x2)

Robust correlation coefficient: 0.3746
Test statistic: 1.7139
p-value: 0.10371 

Call:
pbcor(x = x1, y = x2, beta = 0.1)

Robust correlation coefficient: 0.7966
Test statistic: 5.5909
p-value: 3e-05 

Call:
wincor(x = x1, y = x2)

Robust correlation coefficient: 0.2651
Test statistic: 1.1665
p-value: 0.27046 

Call:
wincor(x = x1, y = x2, tr = 0.1)

Robust correlation coefficient: 0.7804
Test statistic: 5.2947
p-value: 0.00011 

Loading required package: reshape
Call:
pball(x = hangwide)

Robust correlation matrix:
       1      2      3
1 1.0000 0.3746 0.5493
2 0.3746 1.0000 0.7636
3 0.5493 0.7636 1.0000

p-values:
        1       2       3
1      NA 0.10371 0.01212
2 0.10371      NA 0.00009
3 0.01212 0.00009      NA


Test statistic H: 3.063125e+266, p-value = 0

Call:
winall(x = hangwide)

Robust correlation matrix:
       1      2      3
1 1.0000 0.2651 0.4875
2 0.2651 1.0000 0.6791
3 0.4875 0.6791 1.0000

p-values:
        1       2       3
1      NA 0.27046 0.03935
2 0.27046      NA 0.00284
3 0.03935 0.00284      NA

WRS2 documentation built on May 2, 2019, 4:46 p.m.