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modi  

Multivariate Outlier Detection and Imputation for Incomplete Survey Data
View on CRAN: Click here


Download and install modi package within the R console
Install from CRAN:
install.packages("modi")

Install from Github:
library("remotes")
install_github("cran/modi")

Install by package version:
library("remotes")
install_version("modi", "0.1.2")



Attach the package and use:
library("modi")
Maintained by
Beat Hulliger
[Scholar Profile | Author Map]
First Published: 2018-11-20
Latest Update: 2023-03-14
Description:
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) .
How to cite:
Beat Hulliger (2018). modi: Multivariate Outlier Detection and Imputation for Incomplete Survey Data. R package version 0.1.2, https://cran.r-project.org/web/packages/modi. Accessed 04 May. 2025.
Previous versions and publish date:
0.1.0 (2018-11-20 14:10), 0.1.1 (2023-03-03 15:20)
Other packages that cited modi R package
View modi citation profile
Other R packages that modi depends, imports, suggests or enhances
Complete documentation for modi
Functions, R codes and Examples using the modi R package
Some associated functions: BEM . EA.dist . EAdet . EAimp . EM.normal . ER.normal . ER . GIMCD . MDmiss . POEM . PlotMD . TRC . Winsimp . bushfire . bushfire.weights . bushfirem . ind.dij . ind.dijs . lival . modi . nz.min . plotIT . psi.lismi . sepe . sweep.operator . weighted.quantile . weighted.var . weightsum . 
Some associated R codes: BEM.R . EAdet.R . EAimp.R . ER.R . GIMCD.R . MDmiss.R . POEM.R . TRC.R . data.R . modi-internal.R . modi.R . plotIT.R . plotMD.R . weighted.quantile.R . weighted.var.R . winsimp.R .  Full modi package functions and examples
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