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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 |
| Reference manual: | pmledecon.pdf |
| 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 imports: | DBNMFrank |
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These binaries (installable software) and packages are in development.
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