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Kernelheaping
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Download and install Kernelheaping package within the R console
Install from CRAN:
install.packages("Kernelheaping")
Install from Github:
library("remotes")
install_github("cran/Kernelheaping")
Install by package version:
library("remotes")
install_version("Kernelheaping", "2.3.0")
Attach the package and use:
library("Kernelheaping")
Maintained by
Marcus Gross
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-01-27
Latest Update: 2022-01-26
Description:
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.
How to cite:
Marcus Gross (2015). Kernelheaping: Kernel Density Estimation for Heaped and Rounded Data. R package version 2.3.0, https://cran.r-project.org/web/packages/Kernelheaping. Accessed 28 Jan. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for Kernelheaping
Functions, R codes and Examples using
the Kernelheaping R package
Some associated functions: Kernelheaping . createSim.Kernelheaping . dbivr . dclass . dheaping . dshape3dProp . dshapebivr . dshapebivrProp . plot.Kernelheaping . plot.bivrounding . sim.Kernelheaping . simSummary.Kernelheaping . students . summary.Kernelheaping . toOtherShape . tracePlots .
Some associated R codes: Kernelheaping.R . datasets.R . functions.R . Full Kernelheaping package functions and examples
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