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We hope you find these books useful for your work and especially the additional resources that are available here.

Hierarchical statistical models break apart a complex statistical model into a series of linked, less complex submodels by factorizing the likelihood into a series of conditional probability statements. Hierarchical models have many advantages, but the biggest two are arguably:

- They often make the fitting of a complex model easier.
- They represent a principled approach to statistical modeling where, instead of doing relatively brain-free curve-fitting exercises, you think about the processes that likely gave raise to your data set and then represent them in your model. The result is often a more science-based model. And the act of hierarchical modeling almost enforces a clearer thinking about a scientific problem than does the application of some out-of-the-box statistical procedure.

Our books apply the principles of hierarchical modeling to a large range of problems and provide countless
worked example analyses using both likelihood and Bayesian inference, and for the latter using the highly popular
Bayesian BUGS modeling software (originally *WinBUGS* and now *JAGS*).

- Royle & Dorazio, 2008, Hierarchical Modeling and Inference in Ecology
- Kéry, 2010, Introduction to WinBUGS for Ecologists
- Kéry & Schaub, 2012 (BPA), Bayesian Population Analysis using WinBUGS
- Royle et al., 2014 (SCR), Spatial Capture Recapture
- Kéry & Royle, 2016 (AHM1), Applied Hierarchical Modeling in Ecology, Vol 1
- Kéry & Royle, 2021 (AHM2), Applied Hierarchical Modeling in Ecology, Vol 2
- Schaub & Kéry, 2021 (IPM), Integrated Population Models

- unmarked - Unmarked package help forum
- HMecology - Hierarchical Modeling in Ecology
- scr - Spatially explicit capure-recapture
- phidot.org - Wildlife ecology software help forum
- JAGS - JAGS: Just Another Gibbs Sampler forum
- Nimble - Latest and very actively developed BUGS-language software

- unmarked - Models for Data from Unmarked Animals
- AHMbook - Functions and Data for the Book "Applied Hierarchical Modeling in Ecology" Vols 1 and 2
- jagsUI - A Wrapper Around 'rjags' to Streamline 'JAGS' Analyses
- wiqid - Quick and Dirty Estimates for Wildlife Populations

- AHM_code - up-to-date code for both AHM1 and AHM2
- unmarked - code for the unmarked package
- AHMbook - commented code for the AHMbook package
- jagsUI - R package to Run JAGS (Just Another Gibbs Sampler) analyses from within R

- ubms package - Similar to
*unmarked*, but fits models with*Stan*and allows estimation of additional random effects (of site, year, etc.) - IPMbook package