The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

PartCensReg: Estimation and Diagnostics for Partially Linear Censored Regression Models Based on Heavy-Tailed Distributions

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

Documentation:

Reference manual: PartCensReg.pdf

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PartCensReg to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.