stats_from_distribution: Estimate various statistics
In binsmooth: Generate PDFs and CDFs from Binned Data

Description Usage Arguments Details Value Author(s) References Examples

View source: R/stats_from_distribution.R

Estimates the mean, variance, standard deviation, Gini coefficient, and Theil index from a smoothed distribution.

1	stats_from_distribution(binFit)

binFit

A list as returned by splinebins, stepbins, or rsubbins. (Alternatively, a list containing a PDF of non-negative support, its CDF, and an upper bound for the support of the PDF.)

The mean and variance are calculated from the CDF. For details on the other statistics, see gini and theil.

A vector of five statistics.

David J. Hunter and McKalie Drown

Paul T. von Hippel, David J. Hunter, McKalie Drown. Better Estimates from Binned Income Data: Interpolated CDFs and Mean-Matching, Sociological Science, November 15, 2017. https://www.sociologicalscience.com/articles-v4-26-641/

# 2005 ACS data from Cook County, Illinois
binedges <- c(10000,15000,20000,25000,30000,35000,40000,45000,
              50000,60000,75000,100000,125000,150000,200000,NA)
bincounts <- c(157532,97369,102673,100888,90835,94191,87688,90481,
               79816,153581,195430,240948,155139,94527,92166,103217)
stepfit <- stepbins(binedges, bincounts, 76091)
splinefit <- splinebins(binedges, bincounts, 76091)
stats_from_distribution(stepfit)
stats_from_distribution(splinefit) # More accurate