logmnl<- function(X,y,nsize,nxvar,nhh,beta){
#Function evaluates the log-likelihood of multinimial logit model
#X is of dimension X(nsize,nxvar,nhh) and y(nsize,nhh)
# nsize=number of alternatives
# nxvar=number of x variables
# nhh=number of observations
df=read.table("TS_3part.dat",header=TRUE)
inp=as.matrix(df)
y=as.numeric(inp[,1])
+ nsize=3
+ nxvar=4
+ nhh=length(y)
X=createX(p=p,na=1,Xa=data[,3:8],nd=NULL,Xd=NULL,INT=TRUE,base=1)
+ xp<-array(0,dim=c(nsize))
+ logprob<-0
+ for(i in 1:nhh)
+ {
+ for(j in 1:nsize)
+ {
+ xp[j]<-exp(t(X[j,,i]) %*% beta)
+ }
+ denom=sum(xp)
+ for(j in 1:nsize)
+ {
+ if(y[j,i]==1) prob=xp[j]/denom
+ }
+ logprob=logprob+log(prob)
+ }
+ logprob
+ }