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<section id="community">
<h1>Community<a class="headerlink" href="#community" title="Permalink to this heading">¶</a></h1>
<p>This page highlights community projects that involve CmdStanPy. Check them out!</p>
<section id="project-templates">
<h2>Project templates<a class="headerlink" href="#project-templates" title="Permalink to this heading">¶</a></h2>
<p>Templates are a great way to piggy back on other users’ work, saving you time
when you start a new project.</p>
<ul class="simple">
<li><p><a class="reference external" href="https://github.com/teddygroves/bibat">bibat</a>
A batteries-included template for Bayesian statistical analysis projects.</p></li>
<li><p><a class="reference external" href="https://github.com/WardBrian/cookiecutter-cmdstanpy-wrapper">cookiecutter-cmdstanpy-wrapper</a>
A cookiecutter template using Stan models in Python packages, including
the ability to pre-compile the model as part of the package distribution.</p></li>
</ul>
</section>
<section id="software">
<h2>Software<a class="headerlink" href="#software" title="Permalink to this heading">¶</a></h2>
<ul class="simple">
<li><p><a class="reference external" href="https://github.com/facebook/prophet">Prophet</a> A procedure for forecasting
time series data based on an additive model where non-linear trends are fit
with yearly, weekly, and daily seasonality, plus holiday effects.</p></li>
<li><p><a class="reference external" href="https://github.com/arviz-devs/arviz">ArviZ</a> A Python package (with a
<a class="reference external" href="https://julia.arviz.org/stable/">Julia interface</a>) for exploratory analysis of
Bayesian models. Includes functions for posterior analysis, data storage,
model checking, comparison and diagnostics.</p></li>
<li><p><a class="reference external" href="https://github.com/roualdes/bridgestan">BridgeStan</a> A project which provides efficient
in-memory access through Python, Julia, and R to the methods of a Stan model, including
log densities, gradients, Hessians, and constraining and unconstraining transforms.</p></li>
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