fastR (version 1.1)

Correlations: 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", a = 0.05, rho = 0)

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.

a

The significance level used for the confidence intervals.

rho

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

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.

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.

See Also

allbetas, univglms, cova, cora

Examples

x <- matrix( rnorm(100 * 10000), ncol = 10000 )
y <- rnorm(100)
r <- cor(y, x)  ## correlation of y with each of the xs
a <- allbetas(y, x)  ## the coefficients of each simple linear regression of y with x
b <- correls(y, x)