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pmledecon  

Deconvolution Density Estimation using Penalized MLE
View on CRAN: Click here


Download and install pmledecon package within the R console
Install from CRAN:
install.packages("pmledecon")

Install from Github:
library("remotes")
install_github("cran/pmledecon")

Install by package version:
library("remotes")
install_version("pmledecon", "0.2.1")



Attach the package and use:
library("pmledecon")
Maintained by
Yun Cai
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-08-23
Latest Update: 2022-05-30
Description:
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.
How to cite:
Yun Cai (2021). pmledecon: Deconvolution Density Estimation using Penalized MLE. R package version 0.2.1, https://cran.r-project.org/web/packages/pmledecon. Accessed 06 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:42), 0.1.0 (2021-08-23 12:50), 0.2.0 (2022-05-30 04:10)
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Complete documentation for pmledecon
Functions, R codes and Examples using the pmledecon R package
Some associated functions: pmledecon . 
Some associated R codes: pmledecon.R .  Full pmledecon package functions and examples
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