ArviZ a unified library for exploratory analysis of Bayesian models in Python

Kumar, Ravin; Carroll, Colin; Hartikainen, Ari; Martín, Osvaldo Antonio

info:eu-repo/semantics/article

Fecha

2019-01-15

Registro en:

Kumar, Ravin; Carroll, Colin; Hartikainen, Ari; Martín, Osvaldo Antonio; ArviZ a unified library for exploratory analysis of Bayesian models in Python; Journal of Open Source Software; Journal of Open Source Software; 4; 33; 15-1-2019; 1143-1147

2475-9066

http://hdl.handle.net/11336/114615

CONICET Digital

CONICET

https://repositorioslatinoamericanos.uchile.cl/handle/2250/4349462

Autor

Kumar, Ravin

Carroll, Colin

Hartikainen, Ari

Martín, Osvaldo Antonio

Institución

Consejo Nacional de Investigaciones Científicas y Tecnológicas (Argentina)

Resumen

ArviZ is a Python package for exploratory analysis of Bayesian models. ArviZ aims to be a package that integrates seamlessly with established probabilistic programming languages like PyStan, PyMC, Edward, emcee, Pyro and easily integrated with novel or bespoke Bayesian analyses. Where the aim of the probabilistic programming languages is to make it easy to build and solve Bayesian models, the aim of the ArviZ library is to make it easy to process and analyze the results from the Bayesian models.

Materias

BAYESIAN STATISTICS

VISUALIZATION

PYTHON

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