PartCensReg (1.39)

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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) but considering the SMN family.

Maintainer: Marcela Nunez Lemus
Author(s): Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos

License: GPL (>= 2)

Uses: Matrix, optimx, ssym, AER, SMNCensReg

Released over 1 year ago.

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