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function series mlogitlogprobs(series y, matrix X, matrix theta)
set warnings off
scalar n = max(y)
scalar k = cols(X)
matrix b = mshape(theta,k,n)
matrix tmp = X*b
series ret = -ln(1 + sumr(exp(tmp)))
loop for i=1..n --quiet
series x = tmp[,i]
ret += (y=$i) ? x : 0
endloop
return ret
end function
# Replicate the multinomial logit example from Table 15.2 in
# Wooldridge's panel data book (2002a).
# We first do this manually using gretl's mle command, then
# show the result from gretl's built-in logit command
open keane.gdt
# for the manual variant the dep. var. must be 0-based
status = status - 1
# and we must exclude NAs
smpl (year=87 && ok(status)) --restrict
matrix X = { const, educ, exper, expersq, black }
scalar k = cols(X)
matrix theta = zeros(2*k, 1)
mle ll = mlogitlogprobs(status,X,theta)
params theta
end mle --verbose --hessian
# Compare the built-in command (in this case we don't need
# status to be 0-based, and NAs are handled correctly)
smpl full
status = status + 1
smpl (year=87) --restrict
logit status 0 educ exper expersq black --multinomial
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