summary.Kernelheaping

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

object

Prints some descriptive statistics (means and quantiles) for the estimated rounding, bias and acceleration (beta) parameters

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 is supported.

summary.Kernelheaping: Prints some descriptive statistics (means and quantiles) for the estimated rounding, bias and acceleration (beta) parameters

Description

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