confint_betas: Compute Confidence Intervals for Estimated Coefficients

In ryan-heslin/RegLesson: Linear Regression from Scratch

Compute Confidence Intervals for Estimated Coefficients

Description

Compute Confidence Intervals for Estimated Coefficients

Usage

confint_betas(
  betas,
  MSE,
  n,
  p = NROW(covariance),
  covariance,
  alpha = 0.05,
  simultaneous = FALSE
)

Arguments

betas	Vector of estimated beta coefficients. beta+0 is valid.
MSE	Estimated mean squared error for the model
n	Number of rows of the design matrix
p	Number of parameters in the model, counting beta_0.
covariance	Covariance matrix of the estimated coefficients
alpha	Alpha level for the test
simultaneous	Logical. Apply Bonferroni correction for simultaneous intervals? Default FALSE.

Details

This function computes confidence intervals for the estimated beta coefficients of a linear model, optionally simultaneously.

Value

A q \times 3 matrix of the estimated coefficients, with lower and upper bounds for the interval.

ryan-heslin/RegLesson documentation built on Aug. 5, 2022, 9:03 p.m.