lm.ci: Function to calculate confidence intervals for ordinary...

In hdi: High-Dimensional Inference

Function to calculate confidence intervals for ordinary multiple linear regression.

Description

Calculates (classical) confidence intervals for an ordinary multiple linear regression model in the n > p situation.

Usage

lm.ci(x, y, level = 0.95, ...)

Arguments

x	Design matrix (without intercept).
y	Response vector.
level	Coverage level.
...	Additional arguments to be passed to lm.

Details

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

Value

Matrix of confidence interval bounds (not including the intercept).

Author(s)

Lukas Meier

See Also

hdi

Examples

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

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