I am trying to estimate the below log function using maximum likelihood method in R, but I get the following error:
Error in optim(start, f, method = method, hessian = TRUE, ...) : objective function in optim evaluates to length 10 not 1
My attempt was as follows:
Generating data
set.seed(101)
n <- 10
u <- runif(n)
theta1 <- 1
lamba1 <- 0.5
Generating PTIR data using quantile function
x <- function(u, theta1, lamba1) {
(-theta1/(log((1+lamba1)-sqrt((1+lamba1)^2-(4*lamba1*u)))/(2*lamba1)))^(1/(2))
}
x <- x(u = u, theta1 = theta1, lamba1 = lamba1)
Declaring the Log-Likelihood function
LL <- function(theta, lamba) {
R = suppressWarnings((n*log(2))+
(n*log(theta))-(((2)+1)*sum(log(x)))-
(sum(theta/(x^(2))))+
(log(1+lamba-(2*lamba*exp(-theta/(x^(2)))))))
return(-R)
}
mle(LL, start = list(theta = 5, lamba=0.5))
Any advice would be greatly appreciated.
library(stats4)before callingmle, and then ... what isnlog? - Ben Bolkermleand similar functions your objective function needs to return a single, scalar value. Your functionLLapparently returns a vector of length 10 — which is nor surprising, given that your calculation involves a non-scalarx.suppressWarningis a very bad idea in general in numeric calculations: you do not want to ignore warnings. It also helps to cleanly format the equation and to get rid of unnecessary parentheses. - Konrad Rudolphsumyour last term of the equation? - Konrad Rudolph