Correlations {pchc}

Correlation between a vector and a set of variables

Description

Correlation between a vector and a set of variables.

Usage

correls(y, x, type = "pearson", rho = 0, a = 0.05)

Arguments

y

A numerical vector.

x

A matrix with the data.

type

The type of correlation you want. "pearson" and "spearman" are the two supported types because their standard error is easily calculated. For the "groupcorrels" you can also put "kendall" because no hypothesis test is performed in that function.

rho

The value of the hypothesised correlation to be used in the hypothesis testing.

a

The significance level used for the confidence intervals.

Details

The functions uses the built-in function "cor" which is very fast and then includes confidence intervals and produces a p-value for the hypothesis test.

Value

A matrix with 5 column; the correlation, the p-value for the hypothesis test that each of them is eaqual to "rho", the test statistic and the a/2\% lower and upper confidence limits.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

See Also

corpairs, cortest, pcor

Examples

x <- matrix( rnorm(100 * 50 ), ncol = 50)
y <- rnorm(100)
r <- cor(y, x)  ## correlation of y with each of the xs
b <- correls(y, x)