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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Last 30 days
This package has been downloaded 117 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
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Last 365 days
This package has been downloaded 1,648 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 28 downloads.
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Dependencies
- Imports3 packages
- Suggests2 packages