Thanks again.
Now I want to complicate the model. Supose that Y is a vector with 30 data.
Y = c(0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0)
Then the r = sum(Y*log(comb))
Is it possible? I want to discover the variables values
(alpha12,w_g12,w_u12) f
LFRC yahoo.com.br> writes:
>
>
> Dear Ben Bolker,
>
> Thanks a lot for your help.
>
> I have two more questions:
>
> 1) My goal is maximize the function (> r = Y*log(comb)) but the
> parameters found, minimized the function (r = Y*log(comb)).
>
Oh. Oops. Just change the sign ( r =
Dear Ben Bolker,
Thanks a lot for your help.
I have two more questions:
1) My goal is maximize the function (> r = Y*log(comb)) but the
parameters found, minimized the function (r = Y*log(comb)).
2) What this function do?
> model2 <- function(p) {
> do.call("Model",as.list(p))
> }
LFRC yahoo.com.br> writes:
>
>
> Dear,
>
> I'm starting on R language. I would like some help to implement a MLE
> function.
>
> I wish to obtain the variables values (alpha12, w_g12, w_u12) that maximize
> the function LL = Y*ln(alpha12 + g*w_g12 + u*w_u12).
>
You're running into a pro
Dear,
I'm starting on R language. I would like some help to implement a MLE
function.
I wish to obtain the variables values (alpha12, w_g12, w_u12) that maximize
the function LL = Y*ln(alpha12 + g*w_g12 + u*w_u12).
Following the code:
rm(list=ls())
ls()
library(stats4)
Model = functio
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