Package: binequality 1.0.4
Samuel V. Scarpino
binequality: Methods for Analyzing Binned Income Data
Methods for model selection, model averaging, and calculating metrics, such as the Gini, Theil, Mean Log Deviation, etc, on binned income data where the topmost bin is right-censored. We provide both a non-parametric method, termed the bounded midpoint estimator (BME), which assigns cases to their bin midpoints; except for the censored bins, where cases are assigned to an income estimated by fitting a Pareto distribution. Because the usual Pareto estimate can be inaccurate or undefined, especially in small samples, we implement a bounded Pareto estimate that yields much better results. We also provide a parametric approach, which fits distributions from the generalized beta (GB) family. Because some GB distributions can have poor fit or undefined estimates, we fit 10 GB-family distributions and use multimodel inference to obtain definite estimates from the best-fitting distributions. We also provide binned income data from all United States of America school districts, counties, and states.
Authors:
binequality_1.0.4.tar.gz
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binequality_1.0.4.tgz(r-4.4-emscripten)binequality_1.0.4.tgz(r-4.3-emscripten)
binequality.pdf |binequality.html✨
binequality/json (API)
# Install 'binequality' in R: |
install.packages('binequality', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- county_bins - A data set containing binned income for US counties
- school_district_bins - A data set containing the school district data.
- state_bins - A data set containing the binned state data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:a3398c123e. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 09 2024 |
R-4.5-linux | OK | Dec 09 2024 |
Exports:fitFuncgetMidsgetQuantilesParamsginiCoefLRTmakeFitCombmakeIntmakeIntWeightmakeWeightsAICmAvgmidStatsMLDmodelAvgparamFiltrun_GB_familySDLtheilInd
Dependencies:gamlssgamlss.censgamlss.datagamlss.distineqlatticeMASSMatrixnlmesurvival