Estimation and Diagnostics for Partially Linear Censored Regression Models Based on Heavy-Tailed Distributions R package PartCensReg version 1.39 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. Software Imports: ssym, optimx, Matrix Suggests: SMNCensReg, AER Marcela Nunez Lemus <marcela.nunez.lemus@gmail.com> Comprehensive R Archive Network (CRAN) Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos GPL (>= 2) 2018-03-08 application/tgz https://CRAN.R-project.org/package=PartCensReg doi:10.32614/CRAN.package.PartCensReg