rHeckman: Data generation from the Heckman Selection model (Normal or...

In HeckmanEM: Fit Normal or Student-t Heckman Selection Models

Data generation from the Heckman Selection model (Normal or Student-t)

Description

'rHeckman()' generates a random sample from the Heckman selection model (Normal or Student-t).

Usage

rHeckman(x, w, beta, gamma, sigma2, rho, nu = 4, family = "T")

Arguments

x	A covariate matrix for the response y.
w	A covariate matrix for the missing indicator cc.
beta	Values for the beta vector.
gamma	Values for the gamma vector.
sigma2	Value for the variance.
rho	Value for the dependence between the response and missing value.
nu	Value for the degrees of freedom.
family	The family to be used (Normal or T).

Value

Return an object with the response (y) and missing values (cc).

Examples

n <- 100
rho <- .6
cens <- 0.25
nu <- 4
set.seed(20200527)
w <- cbind(1,runif(n,-1,1),rnorm(n))
x <- cbind(w[,1:2])

family <- "T"
c <- qt(cens, df=nu)

sigma2 <- 1
beta <- c(1,0.5)
gamma<- c(1,0.3,-.5)
gamma[1] <- -c*sqrt(sigma2)

data <- rHeckman(x,w,beta,gamma,sigma2,rho,nu,family=family)

HeckmanEM documentation built on July 9, 2023, 6:35 p.m.