I am trying to recover in-sample predictions (fitted values) from a bsts model with a specified poisson response using the bsts
package in R
. The following results in an error: Prediction errors are not supported for Poisson or logit models
.
data("AirPassengers")
# 11 years, monthly data (timestep=monthly) --> 132 observations
Y <- stats::window(AirPassengers, start=c(1949,1), end=c(1959,12))
y <- log10(Y)
ss <- AddLocalLinearTrend(list(), y)
ss <- AddSeasonal(ss, y, nseasons=12, season.duration=1)
bsts.model <- bsts(Y, state.specification=ss, niter=150, family='poisson')
bsts.prediction.errors(bsts.model)
Is there a way to retrieve predictions on model-training data with a poisson model in bsts?
One way to do it is to extract the contribution of each model component at time t and sum them.
But I also posted here, showing that this method didn't necessarily match expectations I had even in the Gaussian case.