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This is just a question of understandig some of your code:
In the file mboostLSS.R it says in Code line 159ff:
## update value of nuisance parameters
## use response(fitted()) as this is much quicker than fitted(, type = response)
for (k in mods[-j])
assign(names(fit)[k], families[[k]]@response(fitted(fit[[k]])),
environment(get("ngradient", environment(fit[[j]]$subset))))
And consequently response(fitted()) is used.
I just wondered whether there is a reason, that in line 130 fitted(, type = response) is used instead of response(fitted())?
The corresponding code ist:
for (k in mods[-j]){
if (!is.null(fit[[k]]))
assign(names(fit)[k], fitted(fit[[k]], type = "response"),
environment(families[[j]]@ngradient))
}
Best
The text was updated successfully, but these errors were encountered:
The reason for changing fitted(, type = response) to response(fitted()) in lines 159ff was that fitted(, type = response) actually calls predict(, type = response) and thus needs to do all computations anew while fitted() simply returns the current accumulated fit.
If we predict in line 130, this is not such a problem as we only have offset models so far. In 159ff we have models with potentially many boosting steps (depending on the current iteration).
Having said this, I think it is not really necessary to change line 130 but it doesn't hurt either. For consistency, we thus modified the code.
This is just a question of understandig some of your code:
In the file mboostLSS.R it says in Code line 159ff:
And consequently response(fitted()) is used.
I just wondered whether there is a reason, that in line 130 fitted(, type = response) is used instead of response(fitted())?
The corresponding code ist:
Best
The text was updated successfully, but these errors were encountered: