[R] Function implemented in R returns the wrong value

[Fernando de Souza Bastos]

Thank you Duncan, it really was that!

Fernando de Souza Bastos
Professor Assistente

Universidade Federal de Viçosa (UFV)

Campus UFV - Florestal

Doutorando em Estatística
Universidade Federal de Minas Gerais (UFMG)
Cel: (31) 99751-6586



2016-12-11 11:25 GMT-02:00 Duncan Murdoch <murdoch.duncan at gmail.com>:

> 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,gam
>> ma7,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
>>
>>         [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>

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