[R] Maximum likelihood estimation

[Jurica Brajković]

Hello, 

I am struggling for some time now to estimate AR(1) process for commodity price time series. I did it in STATA but cannot get a result in R.

The equation I want to estimate is: p(t)=a+b*p(t-1)+error 
Using STATA I get 0.92 for a, and 0.73 for b. 

Code that I use in R is: 
p<-matrix(data$p) # price at time t
lp<-cbind(1,data$lp) # price at time t-1

                                             
mle <- function(theta) {
  sigma2<-theta[1]
  b<- theta[-1]
  n<-length(p)
  e<-p-lp%*%b
  logl<- -(n/2)*log(sigma2)-((t(e)%*%e)/(2*sigma2))
  return(-logl)
  }


out <- optim(c(0,0,0),mle, method = "L-BFGS-B",
    lower = c(0, -Inf, -Inf),
    upper = c(Inf, Inf, Inf))

The "result" I get is: " Error in optim(c(0, 0, 0), mle, method = "L-BFGS-B", lower = c(0, -Inf,:L-BFGS-B needs finite values of 'fn'"

Can somebody spot the mistake?

Many thanks, 

Jurica Brajkovic