restricted_OLS_c: Fast least squares with linear constraint

In RRI: Residual Randomization Inference for Regression Models

Description

This functions fits the regression y ~ X under a linear constraint on the model parameters. The constraint is Q * beta = c where beta are the regression model parameters, and Q, c are inputs.

Usage

restricted_OLS_c(y, X, bhat, Q, c)

Arguments

y	Vector of outcomes.
X	Matrix of covariates (first column should be 1's)
bhat	Unconstrained OLS-fitted coefficients.
Q	Matrix of linear constraints (k x p).
c	Vector of constraint values (k x 1).

Value

Vector of fitted OLS coefficients under linear constraint.

See Also

Advanced Econometrics (Section 1.4, Takeshi Amemiya, 1985)

RRI documentation built on Dec. 19, 2019, 9:06 a.m.