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Package: Kernelheaping
Type: Package
Title: Kernel Density Estimation for Heaped and Rounded Data
Version: 1.6
Date: 2016-04-15
Depends: R (>= 2.15.0), MASS, ks, sparr
Imports: sp, plyr
Author: Marcus Gross
Maintainer: Marcus Gross <marcus.gross@fu-berlin.de>
Description: In self-reported or anonymised data the user often encounters
heaped data, i.e. data which are rounded (to a possibly different degree
of coarseness). While this is mostly a minor problem in parametric density
estimation the bias can be very large for non-parametric methods such as kernel
density estimation. This package implements a partly Bayesian algorithm treating
the true unknown values as additional parameters and estimates the rounding
parameters to give a corrected kernel density estimate. It supports various
standard bandwidth selection methods. Varying rounding probabilities (depending
on the true value) and asymmetric rounding is estimable as well. Additionally,
bivariate non-parametric density estimation for rounded data as well as data aggregated on areas is supported.
License: GPL-2 | GPL-3
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-04-15 14:03:24 UTC; marcusgross
Repository: CRAN
Date/Publication: 2016-04-16 00:09:59
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providing 
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