Package: PartCensReg 1.39

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.

Authors:Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos

PartCensReg_1.39.tar.gz
PartCensReg_1.39.zip(r-4.5)PartCensReg_1.39.zip(r-4.4)PartCensReg_1.39.zip(r-4.3)
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PartCensReg.pdf |PartCensReg.html
PartCensReg/json (API)

# Install 'PartCensReg' in R:
install.packages('PartCensReg', repos = c('https://mnunez5.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1 exports 0.00 score 13 dependencies 2 scripts 143 downloads

Last updated 7 years agofrom:e0752c6876. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-winOKSep 01 2024
R-4.5-linuxOKSep 01 2024
R-4.4-winOKSep 01 2024
R-4.4-macOKSep 01 2024
R-4.3-winOKSep 01 2024
R-4.3-macOKSep 01 2024

Exports:Cens.SMN.PCR

Dependencies:FormulaGIGrvglatticeMatrixnloptrnormalpnumDerivoptimxpracmasandwichssymsurvivalzoo