glm.pval: Function to calculate p-values for a generalized linear...

In hdi: High-Dimensional Inference

Function to calculate p-values for a generalized linear model.

Description

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

Usage

glm.pval(x, y, family = "binomial", verbose = FALSE, ...)

Arguments

x	Design matrix (without intercept).
y	Response vector.
family	As in glm.
verbose	Logical. Should information be printed out if algorithm did not converge?
...	Additional arguments to be passed to glm.

Details

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

Value

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

Author(s)

Lukas Meier

See Also

hdi

Examples

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hdi documentation built on April 18, 2025, 3:01 a.m.