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fBasics (version 4041.97)

correlationTest: 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)

Value

an object from class fHTEST

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.

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

Run this code
# \dontshow{
set.seed(1234)
# }
x <- rnorm(50)
y <- rnorm(50)
  
correlationTest(x, y, "pearson")
correlationTest(x, y, "kendall")

spearmanTest(x, y)

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