Generalization of the Turing Bayesian logistic regression example

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The code in Bayesian Logistic Regression generalizes to arbitrary number of columns/features:

using Turing
using LazyArrays
using Random: seed!
seed!(123)

@model function logreg(X, y; predictors=size(X, 2))
    #priors
    α ~ Normal(0, 2.5)
    β ~ filldist(TDist(3), predictors)

    #likelihood
    y ~ arraydist(LazyArray(@~ BernoulliLogit.(α .+ X * β)))
end;
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