hdi: lm.pval – R documentation

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lm.pval

Function to calculate p-values for ordinary multiple linear regression.

Calculates (classical) p-values for an ordinary multiple linear regression in the n > p situation.

lm.pval(x, y, exact = TRUE, ...)

`x`	Design matrix (without intercept).
`y`	Response vector.
`exact`	Logical. TRUE if p-values based on t-distribution should be calculated. FALSE if normal distribution should be used as approximation.
`...`	Additional arguments to be passed to `lm`.

A model with intercept is fitted but the p-value of the intercept is not reported in the output.

Vector of p-values (not including the intercept).

Lukas Meier

x <- matrix(rnorm(100*5), nrow = 100, ncol = 5)
y <- x[,1] * 2 + x[,2] * 2.5 + rnorm(100)
pval <- lm.pval(x, y)
pval

High-Dimensional Inference

v0.1-7

GPL

Authors

Lukas Meier [aut, cre], Ruben Dezeure [aut], Nicolai Meinshausen [aut], Martin Maechler [aut], Peter Buehlmann [aut]

Initial release

2019-03-27