In self-reported or anonymized 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 is supported.
Details
The most important function is dheaping. See the help and the attached examples on how to use the package.