plot.Kernelheaping

Kernelheaping object produced by <code>dheaping</code> function

optional, if true values X are known (in simulations, for example) the 'Oracle' density estimate is added as well

trueX

additional arguments given to standard plot function

Plot Kernel density estimate of heaped data naively and corrected by partly bayesian model

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) (<doi:10.1093/jssam/smw011>).
Additionally, bivariate non-parametric density estimation for rounded data, Gross, M. et al. (2016) (<doi:10.1111/rssa.12179>),
as well as data aggregated on areas is supported.

Marcus Gross

plot.Kernelheaping: Plot Kernel density estimate of heaped data naively and corrected by partly bayesian model

Description

Usage

Arguments

Value