RegressionAndOtherStories.jl v0.7

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Purpose (once completed, maybe late 2022)

RegressionAndOtherStories.jl contains supporting (Julia) functions and the data files used in "Regression and Other Stories" by Andrew Gelham, Jennifer Hill and Aki Vehtari.

Contents

The supporting functions are intended to be used in (currently) 2 Julia projects (also under development), ROSStanPluto.jl and ROSTuringPluto.jl.

All data files are in .csv format and located in the data directory.

If RegressionAndOtherStories.jl is loaded, the files can be read in as a DataFrame using:

hibbs = CSV.read(ros_datadir("ElectionsEconomy", "hibbs.csv"), DataFrame)

For that purpose ros_datadir() is exported.

If needed, Stata files (.dat) have been converted to .csv files using the scripts in the scripts directory, e.g. see scripts\hdi.jl. To access the Stata files in the R package ROS-Examples RegressionAndOtherStories.jl expects the environment variable JULIA_ROS_HOME to be defined, e.g.:

ENV["JULIA_ROS_HOME"] = expanduser("~/Projects/R/ROS-Examples")

R itself does not necessarily need to be installed for this to work.

If so desired, direct use of the Stata files is also possible as the Stata to .csv file conversion scripts mentioned above show.

Approach

The initial approach attempted in RegressionAndOtherStories.jl (v0.2) and associated projects was different from StatisticalRethinking.jl. But that approach did not work out as expected, so I will switch to a similar setup as in StatisticalRethinking.jl using Requires.jl from v0.3 onwards.

In particular Turing, Stan, Makie and AlgebraOfGraphics, if needed, will all be included using Requires.jl.

Over time I might minimize the use of AlgebraOfGraphics.jl. It is a nice package but also a bit more difficult to tailor (compared to Makie/GLMakie).

For testing purposes the packages enabled using Requires.jl will move to the test section of RegressionAndOtherStories.jl.

In doing this I will move over several important functions from StatisticalRethinking.jl as well, e.g. link().

I expect I can use ParetoSmoothedImportanceSampling.jl and StructuralCausalModels.jl as is.

Issues, comments and questions

Please file issues, comments and questions here.

Pull requests are also welcome.

Versions

Version 9

  1. Switch to extensions
  2. Added simulate function
  3. Added scale_df_cols! (scale! conflicted with Makie and other packages)

Version 0.6.1

  1. Changed back to use DataFrames directly as basis for summaries.
  2. Use getindex to access single elements in summary DataFrames (first argument taken vrom parameters column in df)
  3. For Stan use array() to group nested columns into a matrix. For Turing continue to use nested_column_to_array.

Release 0.5.0

  1. Added DataFrame operatior function (not exported).
  2. Added errorbars_mean and errorbars_draws.
  3. Added nested_column_to_array.
  4. Made model_summary String/Symbol agnostic.

Release 0.4.5

  1. Doc fixes by Pietro Monticone
  2. Added model_summary(::SampleModel).

Release 0.4.x

  1. Model_summary and plot_chains (accept both Symbol and Strings)
  2. Focus on Appendices A and B.
  3. Focus on chapters 4, 5, 6, 7

Versions 0.3.6 - 0.3.10

  1. Fine tuning working with ros_functions and ros_notebooks.

Release 0.3.5

  1. Added maintenance functions for a (large) set of notebooks.

Release 0.3.4

  1. Is tagging using JuliaHub with setting branch name working?

Version 0.3.3

  1. Add initial version of notebook maintenance routines.
  2. Tag this version (if not done by TagBot)

Version 0.3.2

  1. Fix Makie and AoG glue scripts.

Version 0.3.1

  1. StatsFuns compat entry to 1.0.

Version 0.3.0 (under development)

  1. Switch back to using Requires.jl
  2. Switch to using eachindex() where appropriate.
  3. Experimental versions for chapter 3.

Version 0.2.4

  1. Chapter 2 mostly done
  2. Added trankplot function

Version 0.2.0

  1. Support for the 5 examples from chapter 1 done.
  2. Added plot_chains() and model_summary() functions.
  3. Added Makie and AlgebraOfGraphics as dependencies.

Note: Source files for Makie/AoG are all in src/Makie/ to simplify moving those to a separate repo (not my intention right now, but still).

  1. In sync with both ROS[Turing|Stan]Pluto projects tagged 2.3 and up.

Version 0.1.0

  1. Initial commit (to registrate the package for usage in projects).

References

Of course this package is focused on:

  1. Gelman, Hill, Vehtari: Regression and Other Stories

which in a sense is a major update to item 3. below.

There is no shortage of other good books on Bayesian statistics. A few of my favorites are:

  1. Bolstad: Introduction to Bayesian statistics

  2. Bolstad: Understanding Computational Bayesian Statistics

  3. Gelman, Hill: Data Analysis Using Regression and Multilevel/Hierarchical Models

  4. McElreath: Statistical Rethinking

  5. Kruschke: Doing Bayesian Data Analysis

  6. Lee, Wagenmakers: Bayesian Cognitive Modeling

  7. Betancourt: A Conceptual Introduction to Hamiltonian Monte Carlo

  8. Gelman, Carlin, and others: Bayesian Data Analysis

  9. Pearl, Glymour, Jewell: Causal Inference in Statistics: A Primer

  10. Pearl, Judea and MacKenzie, Dana: The Book of Why

  11. Scott Cunningham: Causal Inference - the mixtapes

A good book to understand most of the Julia constructs used in this book is:

  1. Bogumił Kamiński: Julia for Data Analysis.