You're reading from Bayesian Analysis with Python - Third Edition

Product typeBook

Published inJan 2024

Reading LevelExpert

PublisherPackt

ISBN-139781805127161

Edition3rd Edition

Languages

Python

Concepts

Machine Learning

Author (1)

Osvaldo Martin

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...

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Author (1)

Osvaldo Martin

Osvaldo Martin is a researcher at CONICET, in Argentina. He has experience using Markov Chain Monte Carlo methods to simulate molecules and perform Bayesian inference. He loves to use Python to solve data analysis problems. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling. He is an open-source developer, and he contributes to Python libraries like PyMC, ArviZ and Bambi among others. He is interested in all aspects of the Bayesian workflow, including numerical methods for inference, diagnosis of sampling, evaluation and criticism of models, comparison of models and presentation of results.
Read more about Osvaldo Martin

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