[R] If I have 3 parameters, is optim() doing the same thing as Gibbs sampling?

C W tmrsg11 at gmail.com
Thu Dec 10 16:17:47 CET 2015

Hi R list,

I am using optim() to optimize a function with 3 parameters.

#My 1-d toy example: loglikelihood of normal with x=c(2,5,3,7,-3,-2,0),
find MLE of mean.

p1 <- function(theta){
    sum(log(dnorm(c(2,5,3,7,-3,-2,0), mean = theta, sd = 1))) +log(dnorm(
theta, mean = 0.8, sd = 2))
optimize(p1, c(-3, 5), maximum = TRUE)

My question:

If function p1 has 3 parameters, is it doing the same thing as Gibbs

In Gibbs, we optimize parameter 1 while fixing parameter 2 and 3.  Then
optimize 2, fixing 1 and 3. Repeat until convergence.

How does optim() choose random numbers?  I am using the default,

Is optim() drawing numbers from uniform distribution?  Is it picking from
[-Inf, Inf]?  What if I want draw from a prior N(3, 1) instead?

Thanks so much!


	[[alternative HTML version deleted]]

More information about the R-help mailing list