منابع مشابه
High-Breakdown Robust Multivariate Methods
When applying a statistical method in practice it often occurs that some observations deviate from the usual assumptions. However, many classical methods are sensitive to outliers. The goal of robust statistics is to develop methods that are robust against the possibility that one or several unannounced outliers may occur anywhere in the data. These methods then allow to detect outlying observa...
متن کاملHigh Breakdown Multivariate Estimators
In the literature, estimators for regression or multivariate location and dispersion that have been shown to be both consistent and high breakdown are impractical to compute. This paper gives easily computed high breakdown robust √ n consistent estimators, and the applications for these estimators are numerous. For regression, the response plot of the fitted values versus the response is shown ...
متن کاملHigh breakdown estimation methods for Phase I multivariate control charts
The goal of Phase I monitoring of multivariate data is to identify multivariate outliers and step changes so that the estimated control limits are sufficiently accurate for Phase II monitoring. High breakdown estimation methods based on the minimum volume ellipsoid (MVE) or the minimum covariance determinant (MCD) are well suited to detecting multivariate outliers in data. However, they are dif...
متن کاملReview of robust multivariate statistical methods in high dimension.
General ideas of robust statistics, and specifically robust statistical methods for calibration and dimension reduction are discussed. The emphasis is on analyzing high-dimensional data. The discussed methods are applied using the packages chemometrics and rrcov of the statistical software environment R. It is demonstrated how the functions can be applied to real high-dimensional data from chem...
متن کاملRobust Multivariate Methods in Geostatistics
Two robust approaches to principal component analysis and factor analysis are presented. The different methods are compared, and properties are discussed. As an application we use a large geochemical data set which was analyzed in detail by univariate (geo-)statistical methods. We explain the advantages of applying robust multivariate methods.
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ژورنال
عنوان ژورنال: Statistical Science
سال: 2008
ISSN: 0883-4237
DOI: 10.1214/088342307000000087