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.
- Version1.39
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release03/08/2018
Team
Marcela Nunez Lemus
Christian E. Galarza
Larissa Avila Matos
Victor H Lachos
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- Imports3 packages
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