correlationTest {fBasics} | R Documentation |
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, y -
x = rnorm(50)
y = rnorm(50)
## correlationTest -
correlationTest(x, y, "pearson")
correlationTest(x, y, "kendall")
spearmanTest(x, y)