Kernelheaping

Kernel Density Estimation for Heaped and Rounded Data

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: Gross, M. and Rendtel, U. (2016) (<doi:10.1093/jssam/smw011>). Additionally, bivariate non-parametric density estimation for rounded data, Gross, M. et al. (2016) (<doi:10.1111/rssa.12179>), as well as data aggregated on areas is supported.

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Description file content

Package
Kernelheaping
Type
Package
Title
Kernel Density Estimation for Heaped and Rounded Data
Version
2.1.8
Date
2017-10-04
Depends
R (>= 2.15.0), MASS, ks, sparr
Imports
sp, plyr, fastmatch, magrittr, mvtnorm
Author
Marcus Gross [aut, cre], Kerstin Erfurth [ctb]
Maintainer
Marcus Gross
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: Gross, M. and Rendtel, U. (2016) (). Additionally, bivariate non-parametric density estimation for rounded data, Gross, M. et al. (2016) (), as well as data aggregated on areas is supported.
License
GPL-2 | GPL-3
RoxygenNote
6.0.1
NeedsCompilation
no
Packaged
2017-10-10 15:25:16 UTC; mgross
Repository
CRAN
Date/Publication
2017-10-10 16:48:26 UTC

install.packages('Kernelheaping')

2.1.8

12 days ago

Marcus Gross

GPL-2 | GPL-3

Depends on

R (>= 2.15.0), MASS, ks, sparr

Imports

sp, plyr, fastmatch, magrittr, mvtnorm

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