Martin Bayesian Analysis with Python.

Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ
2. Auflage 2018
ISBN: 978-1-78934-966-5
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 356 Seiten

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

Autoren/Hrsg.

Martin, Osvaldo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

Table of Contents - Thinking probabilistically
- Programming probabilistically
- Modeling with Linear Regression
- Generalizing Linear Models
- Model Comparison
- Mixture Models
- Gaussian Processes
- 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.