modi: Multivariate Outlier Detection and Imputation for Incomplete Survey Data

Algorithms for multivariate outlier detection when missing values occur. Algorithms are based on Mahalanobis distance or data depth. Imputation is based on the multivariate normal model or uses nearest neighbour donors. The algorithms take sample designs, in particular weighting, into account. The methods are described in Bill and Hulliger (2016) <doi:10.17713/ajs.v45i1.86>.

Package details

AuthorBeat Hulliger [aut], Martin Sterchi [cre]
MaintainerMartin Sterchi <[email protected]>
LicenseMIT + file LICENSE
Version0.1.0
URL https://github.com/martinSter/modi
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("modi")

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modi documentation built on May 2, 2019, 6:38 a.m.