Hello,
I am new to R and I am trying to estimate a discrete model with three
choices. I am stuck at a point and cannot find a solution.
I have probability functions for occurrence of these choices, and then I
build the likelihood functions associated to these choices and finally I
build the general log-likelihood function.
There are four parameters in the model, three of them are associated to
three discrete choices I mentioned, and one of them is for a binary variable
in the data (t). There are also latent variables but I didn't put them in
this question because if I figure out how to do this, I will be able to add
them as well.
I am not familiar with the syntax I have to write in the likelihood
functions, so I really doubt that they are true. Below I simplify the
problem and provide the code I've written:
# Probabilities for discrete choices for a=3, a=2 and a=1 respectively
P3 <- function(b3,b,t) {
P <- exp(b3+b*(t==1))/(1-exp(b3+b*(t==1)))
return(P)
}
P2 <- function(b2,b,t) {
P <- exp(b2+b*(t==1))/(1-exp(b2+b*(t==1)))
return(P)
}
P1 <- function(b1,b,t) {
P <- exp(b1+b*(t==1))/(1-exp(b1+b*(t==1)))
return(P)
}
# Likelihood functions for discrete choices for a=3, a=2 and a=1
respectively
L3 <- function(b1,b2,b3,b,t) {
P11 <- P1(b1,b,t)
P22 <- P2(b2,b,t)
P33 <- P3(b3,b,t)
L3l <- (P11=1)*(P22=1)*(P33=1)
return(L3l)
}
L2 <- function(b1,b2,b3,b,t) {
P11 <- P1(b1,b,t)
P22 <- P2(b2,b,t)
P33 <- P3(b3,b,t)
L2l <- (P11=1)*(P22=1)*(P33=0)
return(L2l)
}
L1 <- function(b1,b2,b,t) {
P11 <- P1(b1,b,t)
P22 <- P2(b2,b,t)
L1l <- (P11=1)*(P22=0)
return(L1l)
}
# Log-likelihood function
llfn <- function(par,a,t) {
b1 <- par[1]
b2 <- par[2]
b3 <- par[3]
b <- par[4]
lL1 <- log(L1(b1,b2,b,t))
lL2 <- log(L2(b1,b2,b3,b,t))
lL3 <- log(L3(b1,b2,b3,b,t))
llfn <- (a==1)*lL1+(a==2)*lL2+(a==3)*lL3
}
est <- optim(par,llfn, method = c("CG"),control=list(trace=2,maxit=2000),
hessian=TRUE)
And when I run this code I get "cannot coerce type 'closure' to vector of
type 'double'" error.
I will really appreciate your help. Thanks,
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