corpairs: Correlation between pairs of variables

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/corpairs.R

Description

Correlations between pairs of variables.

Usage

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corpairs(x, y, rho = NULL, logged = FALSE, parallel = FALSE) 

Arguments

x

A matrix with real valued data.

y

A matrix with real valued data whose dimensions match those of x.

rho

This can be a vector of assumed correlations (equal to the number of variables or the columns of x or y) to be tested. If this is not the case, leave it NULL and only the correlations will be returned.

logged

Should the p-values be returned (FALSE) or their logarithm (TRUE)? This is taken into account only if "rho" is a vector.

parallel

Should parallel implentations take place in C++? The default value is FALSE.

Details

The paired correlations are calculated. For each column of the matrices x and y the correlation between them is calculated.

Value

A vector of correlations in the case of "rho" being NULL, or a matrix with two extra columns, the test statistic and the (logged) p-value.

Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and Manos Papadakis <papadakm95@gmail.com>.

References

Lambert Diane (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics. 34(1):1-14.

Johnson Norman L., Kotz Samuel and Kemp Adrienne W. (1992). Univariate Discrete Distributions (2nd ed.). Wiley

Cohen, A. Clifford (1960). Estimating parameters in a conditional Poisson distribution. Biometrics. 16:203-211.

Johnson, Norman L. Kemp, Adrianne W. Kotz, Samuel (2005). Univariate Discrete Distributions (third edition). Hoboken, NJ: Wiley-Interscience.

See Also

correls, allbetas, mvbetas

Examples

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x <- matrnorm(100, 100)
y <- matrnorm(100, 100)
system.time( corpairs(x, y) )
a <- corpairs(x, y)
x <- NULL
y <- NULL

Rfast documentation built on Dec. 11, 2021, 9:59 a.m.