rethinking2020

rethinking2020 is a study project of Statistical Rethinking, second edition, by Richard McElreath. [@elreath2020]

Aknowledgement

Many thanks to Richard McElreath who wrote Statistical Rethinking to make Bayesian statistics so interesting.

This study project is inspired by Solomon Kurtz who did wonderful work. It can be found at Solomon Kurtz.

The packages used in this project are as follows.

Package	Comment
rethinking	This R package accompanies a course and book on Bayesian data analysis: McElreath 2020. Statistical Rethinking, 2nd edition.
brms	Used to do pretty much all models and computations.
loo	Used by both `rethinking` and `brms` to compute WAIC and LOO. See section 7.5 in chapter for more details.
posterior	Used to work with the output of Bayesian models.
tidybayes	Bayesian statistics do require a lot of data processing. `tidybayes` is incredibly helpful in providing a constant and efficient way of coding the data processing.
bayestestR	A comprehensive and consistent set of functions to analyze and describe posterior distributions.
tidyverse	The package for data science in general.
extraDistr	has many extra distributions such as BetaBinom, NegBetaBinom, HalfCauchy, ZIP, Pareto, etc. which are useful in real-world applications and usually dispersed among many different packages.
ggmcmc	tool for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis
simpr	tidyverse-friendly framework for generating simulated data, fitting models on simulations, and tidying model results.
modelr	functions that help you create elegant pipelines when modelling
gtools	functions to assist in R programming, including
`logit` and `inv.logit` functions used in many places in this project

Package	Comment
ggdist	`tidybayes` relies heavily on the `ggdist` and reexport very many of it's functions. In addition `ggdist` is useful for both a frequencist as well as a bayesian approach.
bayesplot	Used as complement when `ggdist` and `tidybayes` do not provide a satisfactory solution.
ggplot2	Vizualisations using the grammar of graphics.
scales	Provide the internal scaling infrastructure used by `ggplot2`
paletteer	A nice package to manage color and shape palettes.

Package	Comment
dagitty	Draw and analyse causal diagrams
ggdag	R package to visualize and analyze causal directed acyclic graphs
tidygraph	To manipulate graph data
ggraph	To visualize graphs

Package	Comment
xfun	The function `xfun::cache_rds` is used for caching which is used several times in almost every chapter.