About: ArviZ

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ArviZ (/ˈɑːrvɪz/ AR-vees) is a Python package for exploratory analysis of Bayesian models. When working with Bayesian models there are a series of related tasks that need to be addressed besides inference itself: * Diagnoses of the quality of the inference, this is needed when using numerical methods such as Markov chain Monte Carlo techniques * Model criticism, including evaluations of both model assumptions and model predictions * Comparison of models, including model selection or model averaging * Preparation of the results for a particular audience

Attributes	Values
rdf:type	Thing software schema:CreativeWork work wikidata:Q386724 Software
rdfs:label	ArviZ (en)
rdfs:comment	ArviZ (/ˈɑːrvɪz/ AR-vees) is a Python package for exploratory analysis of Bayesian models. When working with Bayesian models there are a series of related tasks that need to be addressed besides inference itself: * Diagnoses of the quality of the inference, this is needed when using numerical methods such as Markov chain Monte Carlo techniques * Model criticism, including evaluations of both model assumptions and model predictions * Comparison of models, including model selection or model averaging * Preparation of the results for a particular audience (en)
foaf:name	ArviZ (en)
foaf:homepage	https://arviz-devs.github.io/arviz/
name	ArviZ (en)
dcterms:subject	Computational statistics Numerical programming languages Monte Carlo software Free Bayesian statistics software Probabilistic software
Wikipage page ID	62471004 (xsd:integer)
Wikipage revision ID	1122197881 (xsd:integer)
Link from a Wikipage to another Wikipage	PyMC Python (programming language) Computational statistics Julia (programming language) Unix-like Matplotlib Apache License Mac OS X Stan (software) Numerical programming languages Monte Carlo software Free Bayesian statistics software Probabilistic software Statistical package Microsoft Windows Open-source software X86-64 Markov chain Monte Carlo IA-32 Random variate Bayesian Statistics dbr:NumFOCUS
Link from a Wikipage to an external page	http://xarray.pydata.org/en/stable/ https://arviz-devs.github.io/ArviZ.jl/stable/ https://docs.bokeh.org/en/latest/index.html https://mc-stan.org/bayesplot/ https://www.arviz.org/en/latest/ https://arviz-devs.github.io/arviz/ https://cran.r-project.org/web/packages/loo/index.html
sameAs	ArviZ ArviZ
dbp:wikiPageUsesTemplate	dbt:Citation_style dbt:IPAc-en dbt:Infobox_software dbt:More_citations_needed dbt:Multiple_issues dbt:Reflist dbt:Respell dbt:Start_date dbt:Technical dbt:Statistical_software
author	ArviZ Development Team (en)
genre	Statistical package
latest release date	2022-11-16 (xsd:date)
latest release version	0.140000 (xsd:double)
license	Apache License
operating system	Unix-like Mac OS X Microsoft Windows
platform	X86-64 IA-32
programming language	Python (programming language)
released	2018-07-21 (xsd:date)
website	https://arviz-devs.github.io/arviz/
has abstract	ArviZ (/ˈɑːrvɪz/ AR-vees) is a Python package for exploratory analysis of Bayesian models. When working with Bayesian models there are a series of related tasks that need to be addressed besides inference itself: * Diagnoses of the quality of the inference, this is needed when using numerical methods such as Markov chain Monte Carlo techniques * Model criticism, including evaluations of both model assumptions and model predictions * Comparison of models, including model selection or model averaging * Preparation of the results for a particular audience All these tasks are part of the Exploratory analysis of Bayesian models approach, and successfully performing them is central to the iterative and interactive modeling process. These tasks require both numerical and visual summaries. ArviZ offers data structures for manipulating data common in Bayesian analysis, like numerical samples from the posterior, prior predictive and posterior predictive distributions as well as observed data. Additionally, many numerical and visual diagnostics as well as plots are available. The ArviZ name is derived from reading "rvs" (the short form of random variates) as a word instead of spelling it and also using the particle "viz" usually used to abbreviate visualization. ArviZ is an open source project, developed by the community and is an affiliated project of . and it has been used to help interpret inference problems in several scientific domains, including astronomy, neuroscience, physics and statistics. (en)
prov:wasDerivedFrom	wikipedia-en:ArviZ?oldid=1122197881&ns=0
page length (characters) of wiki page	9442 (xsd:nonNegativeInteger)
latest release date	2022-11-16 (xsd:date)
latest release version	0.14.0
release date	2018-07-21 (xsd:date)
computing platform	X86-64 IA-32
genre	Statistical package
license	Apache License
operating system	Unix-like Mac OS X Microsoft Windows
programming language	Python (programming language)
foaf:isPrimaryTopicOf	wikipedia-en:ArviZ
is Link from a Wikipage to another Wikipage of	PyMC
is foaf:primaryTopic of	wikipedia-en:ArviZ

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