binsmooth: Generate PDFs and CDFs from Binned Data

Provides several methods for generating density functions based on binned data. Data are assumed to be nonnegative, but the bin widths need not be uniform, and the top bin may be unbounded. All PDF smoothing methods maintain the areas specified by the binned data. (Equivalently, all CDF smoothing methods interpolate the points specified by the binned data.) An estimate for the mean of the distribution may be supplied as an optional argument, which greatly improves the reliability of statistics computed from the smoothed density functions. Methods include step function, recursive subdivision, and optimized spline.

Author
David J. Hunter and McKalie Drown
Date of publication
2016-08-12 16:46:49
Maintainer
Dave Hunter <dhunter@westmont.edu>
License
MIT + file LICENSE
Version
0.1.0

View on CRAN

Man pages

county_bins
ACS County Income Data, 2006-2010
county_true
ACS County Income Statistics, 2006-2010
rsubbins
Recursive subdivision PDF and CDF fitted to binned data
simcounty
Simulate data to mimic 'county_bins' and 'county_true'
splinebins
Optimized spline PDF and CDF fitted to binned data
stepbins
Step function PDF and CDF fitted to binned data

Files in this package

binsmooth
binsmooth/NAMESPACE
binsmooth/data
binsmooth/data/county_true.rda
binsmooth/data/county_bins.rda
binsmooth/R
binsmooth/R/stepbins.R
binsmooth/R/rsubbins.R
binsmooth/R/splinebins.R
binsmooth/R/simcounty.R
binsmooth/MD5
binsmooth/DESCRIPTION
binsmooth/man
binsmooth/man/county_true.Rd
binsmooth/man/simcounty.Rd
binsmooth/man/splinebins.Rd
binsmooth/man/county_bins.Rd
binsmooth/man/stepbins.Rd
binsmooth/man/rsubbins.Rd
binsmooth/LICENSE