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:	0.2.1
Depends:	R (≥ 3.6.0)
Imports:	stats, splitstackshape, rmutil
Published:	2022-05-30
DOI:	10.32614/CRAN.package.pmledecon
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.html , pmledecon.pdf

Downloads:

Package source:	pmledecon_0.2.1.tar.gz
Windows binaries:	r-devel: pmledecon_0.2.1.zip, r-release: pmledecon_0.2.1.zip, r-oldrel: pmledecon_0.2.1.zip
macOS binaries:	r-release (arm64): pmledecon_0.2.1.tgz, r-oldrel (arm64): pmledecon_0.2.1.tgz, r-release (x86_64): pmledecon_0.2.1.tgz, r-oldrel (x86_64): pmledecon_0.2.1.tgz
Old sources:	pmledecon archive

Reverse dependencies:

Reverse imports:

DBNMFrank

Linking:

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