search for: mlem

...mloglik <- function (beta, Y, L, K) { + n <- length(Y) + sum ( (log(Y)- beta[1]-beta[2]*log(L)-beta[3]*log(K))^2)/2*beta[4]^2 + n/2*log(2*pi)+ n*log(beta[4]) + } Then I did estimates the parameters using nlm ( ) and optim ( ), but the estimates were very bad. I used these codes: > mlem <- nlm (mloglik, c(1,1,1,1), Y=Y, L=L, K=K) > mlem2 <- optim(c(1,1,1,1), mloglik, Y=Y, L=L, K=K, method="BFGS") How I improve the estimates???? What's the best and more simple form for estimate a modelo using the maximum likelihood's method??? Best regards,...