Package: pmledecon 0.2.1

Yun Cai

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.

Authors:Yun Cai [aut, cre], Hong Gu [aut], Tobias Kenney [aut]

pmledecon_0.2.1.tar.gz
pmledecon_0.2.1.tar.gz(r-4.5-noble)pmledecon_0.2.1.tar.gz(r-4.4-noble)
pmledecon_0.2.1.tgz(r-4.4-emscripten)pmledecon_0.2.1.tgz(r-4.3-emscripten)
pmledecon.pdf |pmledecon.html
pmledecon/json (API)

# Install 'pmledecon' in R:
install.packages('pmledecon', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 packages 152 downloads 1 exports 3 dependencies

Last updated 3 years agofrom:f0f21626fd. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 16 2024
R-4.5-linuxNOTEDec 16 2024

Exports:pmledecon

Dependencies:data.tablermutilsplitstackshape