CovNARobust: Robust Location and Scatter Estimation for incomplete data

In rrcovNA: Scalable Robust Estimators with High Breakdown Point for Incomplete Data

Robust Location and Scatter Estimation for incomplete data

Description

Computes a robust multivariate location and scatter estimate with a high breakdown point for incomplete data, using one of the available estimators.

Usage

CovNARobust(x, control, impMeth=c("norm" , "seq", "rseq"))

Arguments

x	a matrix or data frame.
control	a control object (S4) for one of the available control classes, e.g. CovControlMcd-class, CovControlOgk-class, CovControlSest-class, etc., containing estimation options. The class of this object defines which estimator will be used. Alternatively a character string can be specified which names the estimator - one of auto, sde, mcd, ogk, m, mve, sfast, surreal, bisquare, rocke. If 'auto' is specified or the argument is missing, the function will select the estimator (see below for details)
impMeth	select imputation method to use - choose one of "norm" , "seq" or "rseq". The default is "norm"

Details

This function is based on imputation and than estimation with a selected high breakdown point method. Thus first imputation with the selected method will be performed and then the function CovRobustwill be called. For details see CovRobust.

Value

An object derived from a CovRobust object, depending on the selected estimator.

Author(s)

Valentin Todorov [e-mail]

References

V. Todorov, M. Templ and P. Filzmoser. Detection of multivariate outliers in business survey data with incomplete information. Advances in Data Analysis and Classification, 5 37–56, 2011.

Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. <doi:10.18637/jss.v032.i03>.

Examples

data(bush10)
CovNARobust(bush10)
CovNARobust(bush10, CovControlSest())

rrcovNA documentation built on Sept. 11, 2024, 8:12 p.m.