test-correlationTest: Correlation tests

In fBasics: Rmetrics - Markets and Basic Statistics

Correlation tests

Description

Tests if two series are correlated.

Usage

    
correlationTest(x, y, method = c("pearson", "kendall", "spearman"), 
    title = NULL, description = NULL)

pearsonTest(x, y, title = NULL, description = NULL) 
kendallTest(x, y, title = NULL, description = NULL)
spearmanTest(x, y, title = NULL, description = NULL)

Arguments

x, y	numeric vectors of data values.
method	a character string naming which test should be applied.
title	an optional title string, if not specified the input's data name is deparsed.
description	optional description string, or a vector of character strings.

Details

These functions test for association/correlation between paired samples based on the Pearson's product moment correlation coefficient (a.k.a. sample correlation), Kendall's tau, and Spearman's rho coefficients.

pearsonTest, kendallTest, and spearmanTest are wrappers of base R's cor.test with simplified interface. They provide 'exact' and approximate p-values for all three alternatives (two-sided, less, and greater), as well as 95% confidence intervals. This is particularly convenient in interactive use.

Instead of calling the individual functions, one can use correlationTest and specify the required test with argument method.

Value

an object from class fHTEST

References

Conover, W. J. (1971); Practical nonparametric statistics, New York: John Wiley & Sons.

Lehmann E.L. (1986); Testing Statistical Hypotheses, John Wiley and Sons, New York.

See Also

locationTest, scaleTest, varianceTest

Examples

x <- rnorm(50)
y <- rnorm(50)
  
correlationTest(x, y, "pearson")
correlationTest(x, y, "kendall")

spearmanTest(x, y)

fBasics documentation built on Sept. 11, 2024, 6:34 p.m.