Methods for Analyzing Binned Income Data

Documentation for package ‘binequality’ version 1.0.4

binequality-package	Methods for Analyzing Binned Income Data
binequality	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 normalized bin weights.
makeWeightsAIC	A function to calculate AIC weights
mAvg	A simple function to perfom model averaging using pre-calculated weights.
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