HeckmanEM.criteria: Model selection criteria for the Heckman Selection model

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

Model selection criteria for the Heckman Selection model

Description

'HeckmanEM.criteria()' calculates the AIC, AICc, BIC selection criteria for the fitted Heckman selection model.

Usage

HeckmanEM.criteria(obj)

Arguments

obj	An object of the class HeckmanEM.

Value

The calculated AIC, AICc, and BIC for the parameters of the fitted model.

Examples

n <- 100
family <- "T"
nu <- 4
rho <- .6
cens <- .25

set.seed(20200527)
w <- cbind(1,runif(n,-1,1),rnorm(n))
x <- cbind(w[,1:2])
c <- qt(cens, df=nu)

sigma2 <- 1

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

set.seed(1)
datas <- rHeckman(x,w,beta,gamma,sigma2,rho,nu,family=family)
y <- datas$y
cc <- datas$cc

res <- HeckmanEM(y, x, w, cc, nu = 4, family = "Normal", error = 1e-05, iter.max = 500,
                 im = TRUE, criteria = FALSE)
cr <- HeckmanEM.criteria(res)

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