cellHandler {cellWise}R Documentation

cellHandler algorithm

Description

This function flags cellwise outliers in X and imputes them, if robust estimates of the center mu and scatter matrix Sigma are given. When the latter are not known, as is typically the case, one can use the function DDC which only requires the data matrix X. Alternatively, the unknown center mu and scatter matrix Sigma can be estimated robustly from X by the function DI.

Usage

cellHandler(X, mu, Sigma, quant = 0.99)

Arguments

X

X is the input data, and must be an n by d matrix or a data frame.

mu

An estimate of the center of the data

Sigma

An estimate of the covariance matrix of the data

quant

Cutoff used in the detection of cellwise outliers. Defaults to 0.99

Value

A list with components:

Author(s)

J. Raymaekers and P.J. Rousseeuw

References

J. Raymaekers and P.J. Rousseeuw (2020). Handling cellwise outliers by sparse regression and robust covariance. Arxiv: 1912.12446. (link to open access pdf)

See Also

DI

Examples

mu <- rep(0, 3)
Sigma <- diag(3) * 0.1 + 0.9
X <- rbind(c(0.5, 1.0, 5.0), c(-3.0, 0.0, 1.0))
n <- nrow(X); d <- ncol(X)
out <- cellHandler(X, mu, Sigma)
Xres <- X - out$Ximp # unstandardized residual
mean(abs(as.vector(Xres - out$Zres*out$Zres_denom))) # 0
W <- matrix(rep(0,n*d),nrow=n) # weight matrix 
W[out$Zres != 0] <- 1 # 1 indicates cells that were flagged
# For more examples, we refer to the vignette:
vignette("DI_examples")

[Package cellWise version 2.2.5 Index]