Package: PartCensReg
Type: Package
Title: Estimation and Diagnostics for Partially Linear Censored
        Regression Models Based on Heavy-Tailed Distributions
Version: 1.39
Author: Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos
Maintainer: Marcela Nunez Lemus <marcela.nunez.lemus@gmail.com>
Imports: ssym, optimx, Matrix
Suggests: SMNCensReg, AER
Description: 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.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-03-07 19:39:13 UTC; ra143711
Repository: CRAN
Date/Publication: 2018-03-08 23:03:05 UTC
Built: R 4.3.3; ; 2025-01-24 16:54:40 UTC; unix
