collinearity_check: Checking for Perfect Multicollinearity

In penppml: Penalized Poisson Pseudo Maximum Likelihood Regression

Checking for Perfect Multicollinearity

Description

collinearity_check checks for perfect multicollinearity in a model with high-dimensional fixed effects. It calls lfe::demeanlist in order to partial out the fixed effects, and then uses stats::lm.wfit to discard linearly dependent variables.

Usage

collinearity_check(
  y,
  x = NULL,
  fes = NULL,
  hdfetol,
  colcheck_x_fes = TRUE,
  colcheck_x = TRUE
)

Arguments

y	Dependent variable (a numeric vector).
x	Regressor matrix.
fes	List of fixed effects.
hdfetol	Tolerance for the centering, passed on to lfe::demeanlist.
colcheck_x_fes	Logical. If TRUE, this checks whether the independent variables are perfectly explained by the fixed effects drops those that are perfectly explained.
colcheck_x	Logical. If TRUE, this checks collinearity between the independent variables and drops the collinear variables.

Value

A numeric vector containing the variables that pass the collinearity check.

penppml documentation built on Sept. 8, 2023, 5:58 p.m.