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It estimates the parameters of a partially linear regression censored model via maximum penalized likelihood through of ECME algorithm. The model belong to the semiparametric class, that 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-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: | 1.39 |
| Imports: | ssym, optimx, Matrix |
| Suggests: | SMNCensReg, AER |
| Published: | 2018-03-08 |
| Author: | Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos |
| Maintainer: | Marcela Nunez Lemus <marcela.nunez.lemus at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | PartCensReg results |
| Reference manual: | PartCensReg.pdf |
| Package source: | PartCensReg_1.39.tar.gz |
| Windows binaries: | r-devel: PartCensReg_1.39.zip, r-release: PartCensReg_1.39.zip, r-oldrel: PartCensReg_1.39.zip |
| macOS binaries: | r-release (arm64): PartCensReg_1.39.tgz, r-oldrel (arm64): PartCensReg_1.39.tgz, r-release (x86_64): PartCensReg_1.39.tgz, r-oldrel (x86_64): PartCensReg_1.39.tgz |
| Old sources: | PartCensReg archive |
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