Martin Bayesian Analysis with Python

A practical guide to probabilistic modeling
3. Auflage 2024
ISBN: 978-1-80512-541-9
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 394 Seiten

No detailed description available for "Bayesian Analysis with Python".

Autoren/Hrsg.

Martin, Osvaldo

Weitere Mitwirkende

Fonnesbeck, Christopher

Wiecki, Thomas

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz

Inhaltsverzeichnis

Table of Contents - Thinking Probabilistically
- Programming Probabilistically
- Hierarchical Models
- Modeling with Lines
- Comparing Models
- Modeling with Bambi
- Mixture Models
- Gaussian Processes
- Bayesian Additive Regression Trees
- Inference Engines
- Where to Go Next

Über Autor(innen)

Martin Osvaldo:
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.