January 2024
Beginner
394 pages
8h 51m
English
Content preview from Bayesian Analysis with Python - Third Edition
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Index
Akaike Information Criterion (AIC), 193, 196
ArviZ
predictive accuracy, calculating, 212
predictive accuracy, calculating with, 210
Bambi model, interpreting with, 253–255 syntax, 234 using with HSGP, 301 Bartian penguins, 310 Bayes factors, 88, 216, 218, 219 and inference, 228–230 calculating, analytically, 220–222 Savage-Dickey density ratio, 227 Sequential Monte Carlo (SMC), 224 Bayesian additive regression trees (BART) model, 308 Bartian penguins, 311 constant and linear response, 318 individual conditional plots, 315 partial dependence plots (PDP), 313 using, for variable selection, 316 Bayesian analysis posterior, summarizing, 76, 77 Bayesian modeling, ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.