Correlation between pairs of variables
Correlations between pairs of variables.
corpairs(x, y, rho = NULL, logged = FALSE, parallel = FALSE)
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. |
The paired correlations are calculated. For each column of the matrices x and y the correlation between them is calculated.
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.
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>.
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.
x <- matrnorm(100, 100) y <- matrnorm(100, 100) system.time( corpairs(x, y) ) a <- corpairs(x, y) x <- NULL y <- NULL
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