binequality: Methods for Analyzing Binned Income Data
Version 1.0.1

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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AuthorSamuel V. Scarpino, Paul von Hippel, and Igor Holas
Date of publication2016-12-17 01:36:01
MaintainerSamuel V. Scarpino <scarpino@utexas.edu>
LicenseGPL (>= 3.0)
Version1.0.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("binequality")

Man pages

binequality-package: Methods for Analyzing Binned Income Data
county_bins: A data set containing binned income for US counties
fitFunc: A function to fit a parametric distribution to binned data.
getMids: A function to calculate the bin midpoints.
getQuantilesParams: A function to extract the quantiles and parameters
giniCoef: Calculates the Gini coefficient from quantiles
LRT: A function to perform likelihood ratio tests
makeFitComb: A function to transform a list into a dataframe
makeInt: A function to create a survival object from bin counts.
makeIntWeight: A function to create a survival object from bin counts and...
makeWeightsAIC: A function to calculate AIC weights
mAvg: A simple function to perfom model averaging using...
midStats: A function to calculate statistics using bin midpoints
MLD: A function to calculate the MLD
modelAvg: A function to calculate model averages
paramFilt: A function to filter models based on estimated parameters
run_GB_family: A function to fit a parametric distributions to binned data.
school_district_bins: A data set containing the school district data.
SDL: A function to calculate the SDL
state_bins: A data set containing the binned state data.
theilInd: A function to calculate the Theil

Functions

LRT Man page Source code
MLD Man page Source code
SDL Man page Source code
binequality Man page
binequality-package Man page
county_bins Man page
fitFunc Man page Source code
getMids Man page Source code
getQuantilesParams Man page Source code
giniCoef Man page Source code
mAvg Man page Source code
makeFitComb Man page Source code
makeInt Man page Source code
makeIntWeight Man page Source code
makeWeightsAIC Man page Source code
midStats Man page Source code
modelAvg Man page Source code
paramFilt Man page Source code
run_GB_family Man page Source code
school_district_bins Man page
state_bins Man page
theilInd Man page Source code

Files

inst
inst/CITATION
NAMESPACE
data
data/school_district_bins.rda
data/county_bins.rda
data/state_bins.rda
data/datalist
R
R/makeIntWeight.R
R/fitFunc.R
R/MLD.R
R/modelAvg.R
R/makeWeightsAIC.R
R/SDL.R
R/giniCoef.R
R/mAvg.R
R/makeInt.R
R/midStats.R
R/makeFitComb.R
R/paramFilt.R
R/getMids.R
R/LRT.R
R/theilInd.R
R/getQuantilesParams.R
R/run_GB_family.R
MD5
DESCRIPTION
man
man/makeIntWeight.Rd
man/LRT.Rd
man/SDL.Rd
man/midStats.Rd
man/modelAvg.Rd
man/school_district_bins.Rd
man/MLD.Rd
man/makeInt.Rd
man/fitFunc.Rd
man/county_bins.Rd
man/paramFilt.Rd
man/giniCoef.Rd
man/state_bins.Rd
man/theilInd.Rd
man/makeFitComb.Rd
man/binequality-package.Rd
man/getQuantilesParams.Rd
man/mAvg.Rd
man/run_GB_family.Rd
man/makeWeightsAIC.Rd
man/getMids.Rd
binequality documentation built on May 19, 2017, 1:46 p.m.