make.covTrans: Make a proper covariance matrix

In jackiemauro/hurdleIV:

Description

In these regressions, we need to transform the covariance matrix using the coefficients in our regressions. This function produces that covariance matrix.

Usage

make.covTrans(a, num_endog, gamma, beta, option = "mat", noname = F)

Arguments

a	can be a matrix or vector of what should be included in the covariance matrix
num_endog	the number of endogenous regressors
gamma	a vector of your second stage probit regression parameters
beta	a vector of your second stage linear regression parameters
option	either "mat" if a is a matrix, "vector" if a is all the elements of the matrix but in vector form or "parameters" in which case a should be a list of the important parameters: a = list(rho,tau0,tau1,y_sd,endog_sd)

Value

returns the covariance matrix

jackiemauro/hurdleIV documentation built on May 18, 2019, 7:56 a.m.