Open filipepfarias opened 2 years ago
I'm trying to implement the GP with a Poisson likelihood whose parameter may vary with the observations[^1]: $$ y_i \sim Poisson(e_i exp(f_i))$$ where f_i is the GP. Is this possible?
[^1]: Approximate inference for disease mapping with sparse Gaussian processes, Jarno Vanhatalo, Ville Pietiläinen, Aki Vehtari (Eq. 1)
Hi,
It is not possible right now and having external parameters is something we haven't considered so far but definitely should!
I'm trying to implement the GP with a Poisson likelihood whose parameter may vary with the observations[^1]: $$ y_i \sim Poisson(e_i exp(f_i))$$ where f_i is the GP. Is this possible?
[^1]: Approximate inference for disease mapping with sparse Gaussian processes, Jarno Vanhatalo, Ville Pietiläinen, Aki Vehtari (Eq. 1)