Hello,
When fitting a logit multinomial model with "mlogit" I can retrieve the
response probabilities using
fit$fitted.values (for a given object "fit")
However, I am trying to calculate those response probabilities myself using the
maximum likelihood estimates (i.e. fit$coefficients) given by mlogit.
I have used the model given in Agresti (2002):
Prob_j(x) = exp( linearpredictor_j(x) ) / (1 + sum (linearpredictor(x)))
Which is for a category j the exponential of the linear predictor for category
j divided by 1 + the sum of all logits across categories, aside from the
reference category.
But I cannot get my fitted probabilities calculated using this equation to
match the output of mlogit fit$fitted values.
Can anyone tell me how those fitted values are calculated? Or point me to the
corresponding documentation (which I cannot seem to find by googling!)
Many thanks
Ingrid
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