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 |
| 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 |
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