It estimates the parameters of a partially censored regression model via maximum penalized likelihood through a iterative EM-type algorithm. The model must belong to the semi-parametric family, including a parametric and nonparametric component. The error term considered belongs to the scale-mixture of normal (SMN) distribution, that includes well-known heavy tails distributions as the student's-t distribution among others. To examine the performance of the fitted model, case-deletion and local influence techniques are provided to show its robust aspect against outlying and influential observations. This work is based in Ferreira, C. S., & Paula, G. A. (2017) <doi:10.1080/02664763.2016.1267124> but considering the SMN family.
| Version: | 1.38 |
| Imports: | ssym, optimx, Matrix |
| Suggests: | SMNCensReg, AER |
| Published: | 2018-01-05 |
| Author: | Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos |
| Maintainer: | Marcela Nunez Lemus <ra162510 at ime.unicamp.br> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | PartCensReg results |
| Reference manual: | PartCensReg.pdf |
| Package source: | PartCensReg_1.38.tar.gz |
| Windows binaries: | r-devel: PartCensReg_1.38.zip, r-release: PartCensReg_1.38.zip, r-oldrel: PartCensReg_1.38.zip |
| OS X El Capitan binaries: | r-release: PartCensReg_1.38.tgz |
| OS X Mavericks binaries: | r-oldrel: PartCensReg_1.38.tgz |
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