Package: CoDaImpact 0.1.0

Lukas Dargel

CoDaImpact: Interpreting CoDa Regression Models

Provides methods for interpreting CoDa (Compositional Data) regression models along the lines of "Pairwise share ratio interpretations of compositional regression models" (Dargel and Thomas-Agnan 2024) <doi:10.1016/j.csda.2024.107945>. The new methods include variation scenarios, elasticities, elasticity differences and share ratio elasticities. These tools are independent of log-ratio transformations and allow an interpretation in the original space of shares. 'CoDaImpact' is designed to be used with the 'compositions' package and its ecosystem.

Authors:Lukas Dargel [aut, cre], Christine Thomas-Agnan [aut], Rodrigue Nasr [ctb], Sijia Pan [ctb], Iban Rendo Barreiro [ctb], Shuyao Li [ctb]

CoDaImpact_0.1.0.tar.gz
CoDaImpact_0.1.0.zip(r-4.7)CoDaImpact_0.1.0.zip(r-4.6)CoDaImpact_0.1.0.zip(r-4.5)
CoDaImpact_0.1.0.tgz(r-4.6-any)CoDaImpact_0.1.0.tgz(r-4.5-any)
CoDaImpact_0.1.0.tar.gz(r-4.7-any)CoDaImpact_0.1.0.tar.gz(r-4.6-any)
CoDaImpact_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CoDaImpact/json (API)

# Install 'CoDaImpact' in R:
install.packages('CoDaImpact', repos = c('https://lukece.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lukece/codaimpact/issues

Pkgdown/docs site:https://lukece.github.io

Datasets:
  • car_market - French car market data
  • election - Results of french departmental elections in 2015
  • rice_yields - Data on the rice yields in the Vietnamese provinces
  • toulouse_retail - Simulated retail data for nine shopping malls in the city of Toulouse

On CRAN:

Conda:

4.00 score 1 scripts 206 downloads 14 exports 8 dependencies

Last updated from:087a5122af. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK135
source / vignettesOK160
linux-release-x86_64OK116
macos-release-arm64OK129
macos-oldrel-arm64OK132
windows-develOK82
windows-releaseOK105
windows-oldrelOK70
wasm-releaseOK102

Exports:alralrInvclrclrInvCoDa_pathCoDa_seqilrilrInvImpactslmCoDaShareRatioElasticitiesToSimplexVariationScenarioVariationTable

Dependencies:bayesmcompositionsDEoptimRMASSRcppRcppArmadillorobustbasetensorA

Getting started with CoDaImpact
Introduction | Scalar on composition regression | Rice yield data | Regression step with the compositions package | coef | fitted | residuals | Interpretation tools | Finite increments interpretation | Interpretation with ilr coordinates | Interpretation with clr coordinates | Variation scenario in the simplex space | Infinitesimal increments interpretation | Semi-elasticities | Increments approach | Infinitesimal increment: direction pointing to a vertex | Infinitesimal increment: general direction | Composition on scalar regression | Car market data | Regression step | resid | Variation scenario in real space | Infinitesimal Increments approach | Composition on composition regression | Election data | Finite increments | VariationScenario | Infinitesimal increments | Elasticities | Infinitesimal increment: General direction | References
Rendered fromVignette.Rmdusingknitr::rmarkdown

Last update: 2024-03-22
Started: 2024-01-21

“Pairwise share-ratio interpretations of compositional regression models”
Rendered frompaper_Share_Ratio.Rmdusingknitr::rmarkdown

Last update: 2024-03-08
Started: 2023-08-30