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12 changes: 7 additions & 5 deletions docs/source/index.md
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Expand Up @@ -34,7 +34,9 @@ h3:not(#hero h3) {
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<h2 style="font-size: 60px; font-weight: bold; margin: 2rem auto 0;">ArviZ</h2>
<h3 style="font-weight: bold; margin-top: 0;">Exploratory analysis of Bayesian models</h3>
<p>ArviZ is a Python package for exploratory analysis of Bayesian models. It serves as a backend-agnostic tool for diagnosing and visualizing Bayesian inference.</p>
<p>ArviZ is a modular and flexible Python library implementing methods grounded in well-established statistical principles and providing robust, interpretable diagnostics and visualizations for Bayesian workflow.</p>

ArviZ:

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<strong>Interoperability</strong><br/>
Integrates with all major probabilistic programming libraries: PyMC, CmdStanPy, PyStan, Pyro, NumPyro, and emcee.
Integrates with all major probabilistic programming libraries: PyMC, CmdStanPy, Pyro, NumPyro, and emcee.
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<strong>Large Suite of Visualizations</strong><br/>
Provides over 25 plotting functions for all parts of Bayesian workflow: visualizing distributions, diagnostics, and model checking. See the gallery for examples.
Provides over 30 plotting functions for visualizing distributions, MCMC diagnostics, model checking, model comparison. See the gallery for examples.
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<strong>State of the Art Diagnostics</strong><br/>
Latest published diagnostics and statistics are implemented, tested and distributed with ArviZ.
Modern, theory-grounded diagnostics and statistical tools are implemented, tested and distributed through ArviZ.
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<strong>Flexible Model Comparison</strong><br/>
Includes functions for comparing models with information criteria, and cross validation (both approximate and brute force).
Includes functions for comparing models using fast approximate cross validation and brute force methods.
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