Publication
Title
MATLAB library LIBRA
Author
Abstract
LIBRA stands for library for robust analysis. It is a MATLAB toolbox mainly containing implementations of robust statistical methods. Robust statistics is involved with the detection of aberrant observations, also called outliers. The aim of robust statistical methods is to provide estimates which are not affected by the nonregular observations and which are then able to pinpoint the outliers. The robust methods implemented in LIBRA nowadays cover: univariate location, scale (Qn) and skewness estimation (Medcouple), covariance estimation (FAST MCD), regression (FAST-LTS, MCD regression, depth quantiles), principal component analysis (RAPCA, ROBPCA), principal component regression (RPCR), partial least squares regression (RSIMPLS), classification (RDA, RSIMCA) and several methods to deal with skewed data. Besides that, the toolbox contains various methods for cluster analysis, many graphical diagnostic tools, and classical equivalents of several implemented methods. Only a few of the recently added methods will be highlighted in this paper. The features of the LIBRA functions will be illustrated by means of some real data sets.
Language
English
Source (journal)
Wiley Interdisciplinary Reviews: Computational Statistics
Publication
2010
ISSN
1939-5108
1939-0068
Volume/pages
(2010), p. 509-515
Full text (Publishers DOI)
Full text (publishers version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
VABB-SHW
Record
Identification
Creation 07.07.2010
Last edited 22.11.2016
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