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.
Package details |
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| Author | Yun Cai [aut, cre], Hong Gu [aut], Tobias Kenney [aut] |
| Maintainer | Yun Cai <Yun.Cai@dal.ca> |
| License | GPL (>= 3) |
| Version | 0.2.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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