[R] Help on simple problem with optim

[Berend Hasselman]

It is indeed a negative value for sigma that causes the issue.
You can check this by inserting this line

        if(sigma <= 0 ) cat("Negative sigma=",sigma,"\n")

after the line

        mu <- x %*% beta 

in function llk.mar

Negative values for sigma can be avoided with the use of a transformation
for sigma, forcing it to be always positive.

Make optim use log(sigma) as parameter and transform this to sigma with
sigma <- exp(parm[l]) in llk.mar.
Like this

# 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 <- exp(parm[l])  # <=== transform
        x <- as.matrix(x) 
        mu <- x %*% beta 
        if(sigma <= 0 ) cat("Negative sigma=",sigma,"\n")
        llk <- sum(dnorm(y, mu, sigma,log=TRUE)) 
        return(llk) 
} 

# initial values 
parm <- c(as.vector(coef(fit)),log(summary(fit)$sigma))  # use log(sigma) as
independent parameter

Caveat: transformations often help in situations like this but can lead to
badly scaled problems and are not a universal remedy.

/Berend 

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