CRAN/E | PartCensReg

PartCensReg

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

Installation

About

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.

Key Metrics

Version 1.39
Published 2018-03-08 2251 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Marcela Nunez Lemus

marcela.nunez.lemus@gmail.com

Authors

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

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

PartCensReg archive

Imports

ssym
optimx
Matrix

Suggests

SMNCensReg
AER