Analyzing Data with Cellwise Outliers

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Documentation for package ‘cellWise’ version 2.5.3

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

cellHandler	cellHandler algorithm
cellMap	Draw a cellmap
cellMCD	cellWise minimum covariance determinant estimator
checkDataSet	Clean the dataset
cwLocScat	Estimate location and scatter of data with cellwise weights
data_brands	The brands dataset
data_clothes	The clothes dataset
data_dogWalker	Dog walker dataset
data_dposs	DPOSS dataset
data_glass	The glass dataset
data_mortality	The mortality dataset
data_personality_traits	The personality traits data
data_philips	The philips dataset
data_VOC	VOC dataset
DDC	Detect Deviating Cells
DDCpredict	DDCpredict
DI	Detection-Imputation algorithm
estLocScale	Estimate robust location and scale
generateCorMat	Generates correlation matrices
generateData	Generates artificial datasets with outliers
ICPCA	Iterative Classical PCA
MacroPCA	MacroPCA
MacroPCApredict	MacroPCApredict
outlierMap	Plot the outlier map.
plot_cellMCD	Draw plots based on the cellwise minimum covariance determinant estimator cellMCD
transfo	Robustly fit the Box-Cox or Yeo-Johnson transformation
transfo_newdata	Transform variables based on the output of 'transfo'.
transfo_transformback	Backtransform variables based on the output of 'transfo'.
truncPC	Classical Principal Components by truncated SVD.
unpack	Unpacks cellwise weighted data
weightedEM	Estimates location and scatter on incomplete data with case weights
wrap	Wrap the data.