Package: PartCensReg
Type: Package
Title: Partially Censored Regression Models Based on Heavy-Tailed
        Distributions
Version: 1.38
Author: Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos
Maintainer: Marcela Nunez Lemus <ra162510@ime.unicamp.br>
Imports: ssym, optimx, Matrix
Suggests: SMNCensReg, AER
Description: It estimates the parameters of a partially censored regression model via maximum penalized likelihood through a iterative EM-type algorithm. The model must belong to the semi-parametric family, 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's-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: 2018-01-05 16:39:19 UTC; ra143711
Repository: CRAN
Date/Publication: 2018-01-05 18:28:53 UTC
