Hello again,
You are absolutely right about probabilities.. Thanks for reminding me
about that.
I did exactly how you said but in the end I receive the error : "objective
function in optim evaluates to length 12 not 1".
I checked how llfn give a vector instead of scalar, but couldn't figure
it out.
Can you please tell me how did you obtain those estimates?
Thanks again,
Best,
Marc
Rui Barradas wrote
Hello, again.
Bug report:
1. Your densities can return negative values, 1 - exp(...) < 0.
Shouldn't those be 1 PLUS exp()?
P3 <- function(bx,b3,b,tt) {
P <- exp(bx*x+b3+b*(tt == 1))/(1+exp(bx*x+b3+b*(tt == 1)))
return(P)
}
And the same for P2 and P1?
2. Include 'a' and 'tt' as llfn parameters and call like the following.
llfn <- function(param, a, tt) {
[... etc ...]
return(-llfn)
}
start.par <- rep(0, 5)
est <- optim(start.par, llfn, gr=NULL, a=a, tt=tt)
est
$par
[1] 4.1776294 -0.9952026 -0.7667640 -0.1933693 0.7325221
$value
[1] 0
$counts
function gradient
44 NA
$convergence
[1] 0
$message
NULL
Note the optimum value of zero, est$value == 0
Rui Barradas
infinitehorizon wrote
By the way, in my last post I forgot to return negative of llfn, hence
the llfn will be as follows:
llfn <- function(param) {
bx <- param[1]
b1 <- param[2]
b2 <- param[3]
b3 <- param[4]
b <- param[5]
lL1 <- log(L1(bx,b1,b2,b,tt))
lL2 <- log(L2(bx,b1,b2,b3,b,tt))
lL3 <- log(L3(bx,b1,b2,b3,b,tt))
llfn <- (a==1)*lL1+(a==2)*lL2+(a==3)*lL3
return(-llfn)
}
However, it does not fix the problem, I still receive the same error..