Bura_Cook: Bura_Cook estimator for the estimation of rank(beta_1C)

In yanbowisc/SIMP: Bayesian Simultaneous Partial Envelope Model

Bura_Cook estimator for the estimation of rank(beta_1C)

Description

Bura_Cook estimator for the estimation of rank(beta_1C)

Usage

Bura_Cook(X1C, X1D, X2, Y, sig.level = 0.05)

Arguments

X1C	Design matrix of the continuous part of the predictors of interest. Must have the same number of rows as Y.
X1D	Design matrix of the discrete part of the predictors of interest. Must have the same number of rows as Y.
X2	Design matrix of the nuisance predictors. Must have the same number of rows as Y.
Y	Response matrix. Must have the same number of rows as X.
sig.level	Significance level of the sequence of Chi-squared tests called in Bura-Cook estimator.

Examples

## Not run: 
library(SIMP)
library(Renvlp)  # Load Renvlp package only for wheatprotein dataset.
data(wheatprotein)
set.seed(1)
d <- Bura_Cook(X1C = wheatprotein[, 4:5], X1D = matrix(wheatprotein[, 8], ncol = 1), 
                X2 = wheatprotein[, 6:7], Y = wheatprotein[, 1:3], sig.level = 0.05)

## End(Not run)

yanbowisc/SIMP documentation built on Oct. 30, 2022, 1:33 a.m.