[R] Help on simple problem with optim

[Zhang,Yanwei]

Dear all,

I ran into problems with the function "optim" when I tried to do an mle estimation of a simple lognormal regression. Some warning message poped up saying NANs have been produced in the optimization process. But I could not figure out which part of my code has caused this. I wonder if anybody would help. The code is in the following and the data is in the attachment.


da <- read.table("da.txt",header=TRUE)

# fit with linear regression using log transformation of the response variable
fit <- lm(log(yp) ~ as.factor(ay)+as.factor(lag),data=da)

# define the log likelihood to be maximized over
llk.mar <- function(parm,y,x){
        # parm is the vector of parameters
        # the last element is sigma
        # y is the response
        # x is the design matrix
        l <- length(parm)
        beta <- parm[-l]
        sigma <- parm[l]
        x <- as.matrix(x)
        mu <- x %*% beta
        llk <- sum(dnorm(y, mu, sigma,log=TRUE))
        return(llk)
}

# initial values
parm <- c(as.vector(coef(fit)),summary(fit)$sigma)
y <- log(da$yp)
x <- model.matrix(fit)

op <- optim(parm, llk.mar, y=y,x=x,control=list(fnscale=-1,maxit=100000))


After running the above code, I got the warning message:
Warning messages:
1: In dnorm(x, mean, sd, log) : NaNs produced
2: In dnorm(x, mean, sd, log) : NaNs produced


I would really appreciate if anybody would help to point out the problem with this code or tell me how to trace it down (using "trace"?)?
Many thanks in advance.







Wayne (Yanwei) Zhang
Statistical Research
CNA





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