Kernelheaping (1.6)

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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. Additionally, bivariate non-parametric density estimation for rounded data as well as data aggregated on areas is supported.

Maintainer: Marcus Gross
Author(s): Marcus Gross

License: GPL-2 | GPL-3

Uses: ks, MASS, plyr, sp, sparr

Released over 1 year ago.

6 previous versions



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