covrob_ogk: Robust Location and Scatter Estimation - Ortogonalized...

In privefl/bigutilsr: Utility Functions for Large-scale Data

Robust Location and Scatter Estimation - Ortogonalized Gnanadesikan-Kettenring (OGK)

Description

Computes a robust multivariate location and scatter estimate with a high breakdown point, using the pairwise algorithm proposed by Marona and Zamar (2002) which in turn is based on the pairwise robust estimator proposed by Gnanadesikan-Kettenring (1972).

Usage

covrob_ogk(U, niter = 2, beta = 0.9)

dist_ogk(U, niter = 2, beta = 0.9)

Arguments

U	A matrix with no missing values and at least 2 columns.
niter	Number of number of iterations for the first step of the algorithm, usually 1 or 2 since iterations beyond the second do not lead to improvement.
beta	Coverage parameter for the final reweighted estimate. Default is 0.9.

Value

covrob_ogk(): list of robust estimates, ⁠$cov⁠ and ⁠$center⁠.

dist_ogk(): vector of robust Mahalanobis (squared) distances.

References

Maronna, R.A. and Zamar, R.H. (2002) Robust estimates of location and dispersion of high-dimensional datasets; Technometrics 44(4), 307–317.

Yohai, R.A. and Zamar, R.H. (1998) High breakdown point estimates of regression by means of the minimization of efficient scale JASA 86, 403–413.

Gnanadesikan, R. and John R. Kettenring (1972) Robust estimates, residuals, and outlier detection with multiresponse data. Biometrics 28, 81–124.

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.

See Also

rrcov::CovOgk()

stats::mahalanobis()

Examples

X <- readRDS(system.file("testdata", "three-pops.rds", package = "bigutilsr"))
svd <- svds(scale(X), k = 5)

U <- svd$u
dist <- dist_ogk(U)
str(dist)

privefl/bigutilsr documentation built on Oct. 24, 2024, 1:45 p.m.