Numerical errors in logit normal model using Turing.jl

Specific Domains Probabilistic programming
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12

Please do the following for now. I’ll included this into the PR. Sorry for the inconvenience!

using FillArrays

"""
    MvBinomialLogit(n::Vector{<:Int}, logpitp::Vector{<:Real})

A multivariate binomial logit distribution with `n` trials and logit values of `logitp`.
"""
struct MvBinomialLogit{T<:Real, I<:Int} <: DiscreteMultivariateDistribution
    n::Vector{I}
    logitp::Vector{T}
end

Distributions.length(d::MvBinomialLogit) = length(d.n)

function Distributions.logpdf(d::MvBinomialLogit{<:Real}, ks::Vector{<:Integer})
    return sum(Turing.logpdf_binomial_logit.(d.n, d.logitp, ks))
end

@model normal_logit(n, x) = begin

    n_obs = length(n)

    ## hyperparameters for varying effectgs
    ā ~ Normal(0, 0.5)
    σ_a ~ Truncated(Exponential(3), 0, Inf)

    # varying intercepts for each observation
    a ~ MvNormal(Fill(ā, n_obs), σ_a)

    x ~ MvBinomialLogit(n, a)
end