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#13 Building a Probabilistic Programming Framework in Julia, with Chad Scherrer

Learning Bayesian Statistics

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The Bayesian Inference in Julia

The ease of doing Bayesian inference in Julia comes into play. The way I do posterior predictive checks really leverages that also. There's one called Monte Carlo measurements.jl which represents it as a vector, but the screen representation is the mean plus or minus the standard deviation. When you take, say, like a poster for a given distribution, you get this nice, really easy to read representation. It's all thanks to that package.

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