thanks for this cool little package. I have a feature request/question. In discrete choice models (for example in this paper equation 14 ) we often have a smoothed version of the log sum function. that is, instead of
alpha + log( sum (exp( x - alpha ) ) )
we'd have
alpha + σ log( sum (exp( (x - alpha)/σ ) ) )
I was trying to think how to add this to the package (maybe in my own fork if this turns out non of interest here), but I'm not totally sure where. My best guess would have been to do the division by sigma in places like here, but not totally certain. thanks for any hints!
thanks for this cool little package. I have a feature request/question. In discrete choice models (for example in this paper equation 14 ) we often have a smoothed version of the log sum function. that is, instead of
we'd have
I was trying to think how to add this to the package (maybe in my own fork if this turns out non of interest here), but I'm not totally sure where. My best guess would have been to do the division by sigma in places like here, but not totally certain. thanks for any hints!