Artículo

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

Kumar, Ravin; Carroll, Colin; Hartikainen, Ari; Martín, Osvaldo AntonioIcon
Fecha de publicación: 15/01/2019
Editorial: Journal of Open Source Software
Revista: Journal of Open Source Software
ISSN: 2475-9066
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:

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.
Palabras clave: BAYESIAN STATISTICS , VISUALIZATION , PYTHON
 
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution 2.5 Unported (CC BY 2.5)
Identificadores
URI: http://hdl.handle.net/11336/114615
URL: http://joss.theoj.org/papers/10.21105/joss.01143
DOI: http://dx.doi.org/10.21105/joss.01143
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Articulos(IMASL)
Articulos de INST. DE MATEMATICA APLICADA DE SAN LUIS
Citación
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
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