Source: r-cran-kernelheaping Standards-Version: 4.7.3 Maintainer: Debian R Packages Maintainers Uploaders: Andreas Tille , Section: gnu-r Testsuite: autopkgtest-pkg-r Build-Depends: debhelper-compat (= 13), dh-r, r-base-dev, r-cran-mass, r-cran-ks, r-cran-sparr, r-cran-sp, r-cran-plyr, r-cran-dplyr, r-cran-fastmatch, r-cran-fitdistrplus, r-cran-gb2, r-cran-magrittr, r-cran-mvtnorm, architecture-is-64-bit, architecture-is-little-endian, Vcs-Browser: https://salsa.debian.org/r-pkg-team/r-cran-kernelheaping Vcs-Git: https://salsa.debian.org/r-pkg-team/r-cran-kernelheaping.git Homepage: https://cran.r-project.org/package=Kernelheaping Rules-Requires-Root: no Package: r-cran-kernelheaping Architecture: all Depends: ${R:Depends}, ${misc:Depends}, Recommends: ${R:Recommends}, Suggests: ${R:Suggests}, Description: GNU R 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) (). Additionally, bivariate non- parametric density estimation for rounded data, Gross, M. et al. (2016) (), as well as data aggregated on areas is supported.