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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Kernelheaping.R
\docType{package}
\name{Kernelheaping}
\alias{Kernelheaping}
\title{Kernel Density Estimation for Heaped Data}
\description{
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 \code{\link{dheaping}}. See the help and the attached examples on how to use the package.
}
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