examples.qmd

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title: "Examples"
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NIMBLE provides a rich collection of examples to help you get started with statistical modeling and algorithm development. Examples cover a wide range of topics from basic BUGS model usage to advanced algorithm implementation.

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## Building a model from BUGS code

[Read this example on a new page.](examples/nimble_build_a_model.html)

<iframe src="examples/nimble_build_a_model.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Converting to NIMBLE

[Read this example on a new page.](examples/converting_to_nimble.html)

<iframe src="examples/converting_to_nimble.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Creating a default MCMC

[Read this example on a new page.](examples/nimble_basic_mcmc.html)

<iframe src="examples/nimble_basic_mcmc.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Customizing an MCMC

[Read this example on a new page.](examples/nimble_customizing_mcmc.html)

<iframe src="examples/nimble_customizing_mcmc.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Parallelizing NIMBLE

[Read this example on a new page.](examples/parallelizing_NIMBLE.html)

<iframe src="examples/parallelizing_NIMBLE.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Simulating from a model (quickly!)

[Read this example on a new page.](examples/simulation_from_model.html)

<iframe src="examples/simulation_from_model.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Using linear predictors in a regression model

[Read this example on a new page.](examples/linpred.html)

<iframe src="examples/linpred.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Building a generalized linear mixed model and an MCMC for it

[Read this example on a new page.](examples/nimble_logistic_regression.html)

<iframe src="examples/nimble_logistic_regression.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Variable selection using reversible jump MCMC (RJMCMC)

[Read this example on a new page.](examples/RJMCMC_example.html)

<iframe src="examples/RJMCMC_example.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Restarting an MCMC

[Read this example on a new page.](examples/restart_mcmc.html)

<iframe src="examples/restart_mcmc.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Posterior predictive sampling and other post-MCMC use of samples

[Read this example on a new page.](examples/posterior_predictive.html)

<iframe src="examples/posterior_predictive.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Ecology examples from the book Applied Hierarchical Modeling in Ecology

[Read this example on a new page.](examples/Ecology_Examples.html)

<iframe src="examples/Ecology_Examples.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Writing a new distribution for use in BUGS code: zero-inflated Poisson

[Read this example on a new page.](examples/zero_inflated_poisson.html)

<iframe src="examples/zero_inflated_poisson.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Gaussian process models

[Read this example on a new page.](examples/gaussian_process.html)

<iframe src="examples/gaussian_process.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Conditional autoregressive (CAR) models

[Read this example on a new page.](examples/CAR.html)

<iframe src="examples/CAR.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Item response theory (IRT) models

[Read this example on a new page.](examples/IRT_example.html)

<iframe src="examples/IRT_example.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Maximum likelihood via Monte Carlo Expectation-Maximization (MCEM)

[Read this example on a new page.](examples/pumpMCEM.html)

<iframe src="examples/MLE.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Maximum likelihood (basic example)

[Read this example on a new page.](examples/MLE.html)

<iframe src="examples/MLE.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>

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## Stochastic volatility modeling using a custom distribution

[Read this example on a new page.](examples/stochastic_volatility.html)

<iframe src="examples/stochastic_volatility.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Bayesian nonparametric density estimation

[Read this example on a new page.](examples/bnp_density.html)

<iframe src="examples/bnp_density.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Bayesian nonparametric random effects

[Read this example on a new page.](examples/bnp_raneff.html)

<iframe src="examples/bnp_raneff.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Bayesian nonparametrics with jointly clustered observations

[Read this example on a new page.](examples/bnp_multivariate.html)

<iframe src="examples/bnp_multivariate.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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## Using the Pólya-gamma sampler

[Read this example on a new page.](examples/polya_gamma.html)

<iframe src="examples/polya_gamma.html" width="100%" height="500" style="border: 1px solid #ccc;"></iframe>
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