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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:f0f21626fd. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 16 2024 |
R-4.5-linux | NOTE | Dec 16 2024 |
Exports:pmledecon
Dependencies:data.tablermutilsplitstackshape
Readme and manuals
Help Manual
Help page | Topics |
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Deconvolution density estimation using penalized MLE | pmledecon |