pmledecon: Deconvolution Density Estimation using Penalized MLE

Given a sample with additive measurement error, the package estimates the deconvolution density - that is, the density of the underlying distribution of the sample without measurement error. The method maximises the log-likelihood of the estimated density, plus a quadratic smoothness penalty. The distribution of the measurement error can be either a known family, or can be estimated from a "pure error" sample. For known error distributions, the package supports Normal, Laplace or Beta distributed error. For unknown error distribution, a pure error sample independent from the data is used.

Version: 0.1.0
Depends: R (≥ 3.6.3)
Imports: stats, splitstackshape, rmutil
Published: 2021-08-23
Author: Yun Cai [aut, cre], Hong Gu [aut], Tobias Kenney [aut]
Maintainer: Yun Cai <Yun.Cai at dal.ca>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: pmledecon results

Documentation:

Reference manual: pmledecon.pdf
Vignettes: pmledecon

Downloads:

Package source: pmledecon_0.1.0.tar.gz
Windows binaries: r-devel: pmledecon_0.1.0.zip, r-release: pmledecon_0.1.0.zip, r-oldrel: pmledecon_0.1.0.zip
macOS binaries: r-release (arm64): pmledecon_0.1.0.tgz, r-release (x86_64): pmledecon_0.1.0.tgz, r-oldrel: pmledecon_0.1.0.tgz

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