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binequality

Methods for Analyzing Binned Income Data

v1.0.4 · Nov 5, 2018 · GPL (>= 3.0)

Description

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.

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Maintainer: ‘Samuel V. Scarpino <s.scarpino@northeastern.edu>’

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  Authors@R: c(person(given = c("Samuel", "V."),
                      family = "Scarpino",
                      role = c("aut", "cre"),
                      email = "s.scarpino@northeastern.edu"),
               person(given = "Paul",
                      family = "von Hippel",
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Maintainer: ‘Samuel V. Scarpino <s.scarpino@northeastern.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = c("Samuel", "V."),
                      family = "Scarpino",
                      role = c("aut", "cre"),
                      email = "s.scarpino@northeastern.edu"),
               person(given = "Paul",
                      family = "von Hippel",
                      role = "aut"),
               person(given = "Igor",
                      family = "Holas",
                      role = "aut"))
as necessary.

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as.personList().  Please use c() on person objects instead.
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use bibentry() instead.

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Samuel V. Scarpino <s.scarpino@northeastern.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = c("Samuel", "V."),
                      family = "Scarpino",
                      role = c("aut", "cre"),
                      email = "s.scarpino@northeastern.edu"),
               person(given = "Paul",
                      family = "von Hippel",
                      role = "aut"),
               person(given = "Igor",
                 
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Samuel V. Scarpino <s.scarpino@northeastern.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = c("Samuel", "V."),
                      family = "Scarpino",
                      role = c("aut", "cre"),
                      email = "s.scarpino@northeastern.edu"),
               person(given = "Paul",
                      family = "von Hippel",
                      role = "aut"),
               person(given = "Igor",
                 

Dependency Network

Dependencies Reverse dependencies gamlss gamlss.cens gamlss.dist survival ineq binequality

Version History

new 1.0.4 Mar 9, 2026