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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 |
DOI: | 10.32614/CRAN.package.PartCensReg |
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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