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JuliaPsychometrics / RaschModels.jl

Rasch modeling with all the bells and whistles. Implementations for Rasch model, partial credit model, rating scale model, and its linear extensions (upcoming). Classical and Bayesian estimation.
MIT License
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Add bayesian model fitting via variational inference #21

Open p-gw opened 1 year ago

p-gw commented 1 year ago

Variational inference is supported by Turing.vi() and can be easily implemented using a custom _fit function.

See https://turing.ml/dev/tutorials/09-variational-inference/ for details about VI in Turing.jl

This might require an additional EstimationType in JuliaPsychometrics/AbstractItemResponseModels.jl since VI does return a T <: Distribution not posterior samples or a single point estimate.

p-gw commented 1 year ago

A simple workaround might be to just draw samples from the variational posterior and make it a SamplingEstimate.