On 10/12/2016 2:01 PM, Fernando de Souza Bastos wrote:
The Log.lik function below returns the value '-INF' when it should return
the value -5836.219. I can not figure out the error, does anyone have any
suggestions?
I haven't read it carefully, but a likely problem is that you are using
constructs like log(dnorm(x)) (e.g. log(phi_t0)) instead of dnorm(x, log
= TRUE). The dnorm(x) value will underflow to zero, and taking the log
will give you -Inf. Using the "log = TRUE" argument avoids the underflow.
Duncan Murdoch
rm(list=ls())
library(ssmrob)
data(MEPS2001)
attach(MEPS2001)
n<-nrow(MEPS2001)
Log.lik <- function(par,X,W,y){
n <- length(y)
beta <- par[1:(ncol(X)+1)]
gamma <- par[(ncol(X)+2):(ncol(X)+ncol(W)+2)]
mu1 <- model.matrix(~X)%*%beta
mu2 <- model.matrix(~W)%*%gamma
sigma <- par[(ncol(X)+ncol(W)+3)]
rho <- par[(ncol(X)+ncol(W)+4)]
term0 <- (y-mu1)/sigma
term1 <- ((rho*(term0))+mu2)/sqrt(1-rho^2)
Phi_mu2 <- pnorm(mu2)
phi_t0 <- dnorm(term0)
phi_t1 <- dnorm(term1)
Phi_t0 <- pnorm(term0)
Phi_t1 <- pnorm(term1)
f <- (phi_t0*Phi_t1)/(sigma*Phi_mu2)
#Função log de verossimilhança
return(sum(ifelse(Y2>0,log(phi_t0)+log(Phi_t1)+log(1/sigma),log(1-Phi_mu2))))
}
y <- lnambx
Y2 <- dambexp
X <- cbind(age,female,educ,blhisp,totchr,ins)
W <- cbind(age,female,educ,blhisp,totchr,ins,income)
gamma0=-0.6760544
gamma1=0.0879359
gamma2=0.6626647
gamma3=0.0619485
gamma4=-0.3639377
gamma5=0.7969515
gamma6=0.1701366
gamma7=0.0027078
beta0=5.0440623
beta1=0.2119747
beta2=0.3481427
beta3=0.0187158
beta4=-0.2185706
beta5=0.5399190
beta6=-0.0299875
sigma=1.2710176
rho=-0.1306012
beta=c(beta0,beta1,beta2,beta3,beta4,beta5,beta6)
gamma=c(gamma0,gamma1,gamma2,gamma3,gamma4,gamma5,gamma6,gamma7)
start=c(gamma0,gamma1,gamma2,gamma3,gamma4,gamma5,gamma6,gamma7,beta0,beta1,beta2,beta3,beta4,beta5,beta6,sigma,rho)
Log.lik(start,X=X,W=W,y)
If you run the codes below that are within the programming of the Log.lik
function they compile correctly!
mu1 <- model.matrix(~X)%*%beta
mu2 <- model.matrix(~W)%*%gamma
term0 <- (y-mu1)/sigma
term1 <- ((rho*(term0))+mu2)/sqrt(1-rho^2)
Phi_mu2 <- pnorm(mu2)
phi_t0 <- dnorm(term0)
phi_t1 <- dnorm(term1)
Phi_t0 <- pnorm(term0)
Phi_t1 <- pnorm(term1)
f <- (phi_t0*Phi_t1)/(sigma*Phi_mu2)
sum(ifelse(Y2>0,log(phi_t0)+log(Phi_t1)+log(1/sigma),log(1-Phi_mu2)))
Fernando Bastos
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
