Hi everybody,
I'm interested in evaluating the effect of a continuous variable on the mean
and/or the variance of my response variable. I have built functions
expliciting these and used the 'mle2' function to estimate the coefficients,
as follows:
func.1 <- function(m=62.9, c0=8.84, c1=-1.6)
{
s <- c0+c1*(x)
-sum(dnorm(y, mean=m, sd=s,log=T))
}
m1 <- mle2(func.1, method="SANN")
However, the estimation of the effect of x on the variance of y usually has
dealt some troubles, resulting in no convergencies or sd of estimates
extremely huge. I tried using different optimizers, but I still faced the
some problems.
When I had similar troubles in 'GLMM' statistical universe, I used bayesian
functions to solve this problem, enjoyning the flexibility of different
start points to reach the maximum likelihood estimates. However, I have no
idea which package or which function to use to solve the specific problem
I'm facing now.
Does anyone have a clue?
Thanks in advance
Gustavo Requena
PhD Student - Laboratory of Arthropod Behavior and Evolution
Universidade de Sao Paulo - Brazil
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