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cellWise (version 2.2.2)

Analyzing Data with Cellwise Outliers

Description

Tools for detecting cellwise outliers and robust methods to analyze data which may contain them. Contains the implementation of the algorithms described in Rousseeuw and Van den Bossche (2018) (open access) Hubert et al. (2019) (open access), Raymaekers and Rousseeuw (2019) (open access), Raymaekers and Rousseeuw (2020) (open access), Raymaekers and Rousseeuw (2020) (open access). Examples can be found in the vignettes: "DDC_examples", "MacroPCA_examples", "wrap_examples" and "transfo_examples".

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Version

Install

install.packages('cellWise')

Monthly Downloads

1,203

Version

2.2.2

License

GPL (>= 2)

Maintainer

Jakob Raymaekers

Last Published

November 26th, 2020

Functions in cellWise (2.2.2)

dog_walker

Dog walker dataset
DI

Detection-Imputation algorithm
cellMap

Draw a cellmap
MacroPCApredict

MacroPCApredict
MacroPCA

MacroPCA
cellHandler

cellHandler algorithm
checkDataSet

Clean the dataset
DDC

Detect Deviating Cells
DDCpredict

DDCpredict
ICPCA

Iterative Classical PCA
outlierMap

Plot the outlier map.
truncPC

Classical Principal Components by truncated SVD.
transfo

Robustly fit the Box-Cox or Yeo-Johnson transformation
wrap

Wrap the data.
philips

The philips dataset
estLocScale

Estimate robust location and scale
dposs

DPOSS dataset
mortality

The mortality dataset
glass

The glass dataset