crmReg: Cellwise Robust M-Regression and SPADIMO

Method for fitting a cellwise robust linear M-regression model (CRM, Filzmoser et al. (2020) <DOI:10.1016/j.csda.2020.106944>) that yields both a map of cellwise outliers consistent with the linear model, and a vector of regression coefficients that is robust against vertical outliers and leverage points. As a by-product, the method yields an imputed data set that contains estimates of what the values in cellwise outliers would need to amount to if they had fit the model. The package also provides diagnostic tools for analyzing casewise and cellwise outliers using sparse directions of maximal outlyingness (SPADIMO, Debruyne et al. (2019) <DOI:10.1007/s11222-018-9831-5>).

Package details

AuthorPeter Filzmoser [aut], Sebastiaan Hoppner [aut, cre], Irene Ortner [aut], Sven Serneels [aut], Tim Verdonck [aut]
MaintainerSebastiaan Hoppner <sebastiaan.hoppner@gmail.com>
LicenseGPL (>= 2)
Version1.0.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("crmReg")

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crmReg documentation built on Jan. 13, 2021, 12:40 p.m.