r-cran-kernelheaping - 2.3.0-1 main

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.