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cellWise (version 2.2.3)

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", "transfo_examples" and "DI_examples".

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Version

Install

install.packages('cellWise')

Monthly Downloads

8,658

Version

2.2.3

License

GPL (>= 2)

Maintainer

Jakob Raymaekers

Last Published

December 3rd, 2020

Functions in cellWise (2.2.3)

ICPCA

Iterative Classical PCA
MacroPCA

MacroPCA
DDCpredict

DDCpredict
cellMap

Draw a cellmap
DI

Detection-Imputation algorithm
cellHandler

cellHandler algorithm
checkDataSet

Clean the dataset
MacroPCApredict

MacroPCApredict
DDC

Detect Deviating Cells
data_VOC

VOC dataset
outlierMap

Plot the outlier map.
transfo

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

Wrap the data.
data_dposs

DPOSS dataset
truncPC

Classical Principal Components by truncated SVD.
data_dogWalker

Dog walker dataset
generateCorMat

Generates correlation matrices
estLocScale

Estimate robust location and scale
generateData

Generates artificial datasets with outliers
data_philips

The philips dataset
data_glass

The glass dataset
data_mortality

The mortality dataset