Description: A class of frequently used Bayesian parametric and nonparametric model structures, as well as a set of tools for common analytical tasks. Structures include linear Gaussian systems, Gaussian and Normal-Inverse-Wishart conjugate structure, Gaussian and Normal-Inverse-Gamma conjugate structure, Categorical and Dirichlet conjugate structure, Dirichlet Process on positive integers, Dirichlet Process in general, Hierarchical Dirichlet Process ... Tasks include updating posteriors, sampling from posteriors, calculating marginal likelihood, calculating posterior predictive densities, sampling from posterior predictive distributions, calculating "Maximum A Posteriori" (MAP) estimates ... See Murphy (2012, <doi:10.1080/09332480.2014.914768>), Koller and Friedman (2009, <doi:10.1017/s0269888910000275>) and Andrieu, de Freitas, Doucet and Jordan (2003, <doi:10.1023/A:1020281327116>) for more information. See <https://chenhaotian.github.io/Bayesian-Bricks/> to get started.

Description: A set of frequently used Bayesian parametric and nonparametric model structures, as well as a set of tools for common analytical tasks. Structures include linear Gaussian systems, Gaussian and Normal-Inverse-Wishart conjugate structure, Gaussian and Normal-Inverse-Gamma conjugate structure, Categorical and Dirichlet conjugate structure, Dirichlet Process on positive integers, Dirichlet Process in general, Hierarchical Dirichlet Process ... Tasks include updating posteriors, sampling from posteriors, calculating marginal likelihood, calculating posterior predictive densities, sampling from posterior predictive distributions, calculating "Maximum A Posteriori" (MAP) estimates ... See <https://chenhaotian.github.io/Bayesian-Bricks/> to get started.

Title: Hierarchical Bayesian Analysis of North American BBS Data
Authors@R: c(person("Brandon P.M.", "Edwards", role = c("aut", "cre"),
person("Adam C.", "Smith", role = "aut",
Imports: progress, jagsUI, ggrepel, geofacet, ggplot2, stringr,
grDevices, rgdal, dplyr, sf, tools, latticeExtra, rappdirs
Description: The North American Breeding Bird Survey (BBS) is a long-running
program that seeks to monitor the status and trends of the breeding birds in
North America. Since its start in 1966, the BBS has accumulated over 50 years
of data for over 300 species of North American Birds. Given the temporal and
spatial structure of the data, hierarchical Bayesian models are used to assess
the status and trends of these 300+ species of birds. 'bbsBayes' allows you to perform
hierarchical Bayesian analysis of BBS data. You can run a full
model analysis for one or more species that you choose, or you can take
more control and specify how the data should be stratified, prepared
for 'JAGS', or modelled. The functions provided here allow you to replicate
analyses performed by the United State Geological Survey (USGS, see Link
and Sauer (2011) <doi:10.1525/auk.2010.09220>) and Canadian Wildlife Service
Author: Brandon P.M. Edwards [aut, cre],
Maintainer: Brandon P.M. Edwards <edwardsb@uoguelph.ca>