0000000000269388

AUTHOR

Seija Sirkiä

showing 5 related works from this author

k-Step shape estimators based on spatial signs and ranks

2010

In this paper, the shape matrix estimators based on spatial sign and rank vectors are considered. The estimators considered here are slight modifications of the estimators introduced in Dümbgen (1998) and Oja and Randles (2004) and further studied for example in Sirkiä et al. (2009). The shape estimators are computed using pairwise differences of the observed data, therefore there is no need to estimate the location center of the data. When the estimator is based on signs, the use of differences also implies that the estimators have the so called independence property if the estimator, that is used as an initial estimator, has it. The influence functions and limiting distributions of the es…

Statistics and ProbabilityInfluence functionCovariance matrixApplied MathematicsAffiinisti ekvivarianttitehokkuusspatiaalinen järjestyslukuEstimatorSpatial signEfficiencyM-estimatorEfficient estimatorinfluenssifunktioExtremum estimatorHeavy-tailed distributionStatisticsAffine equivarianceStatistics Probability and UncertaintySpatial rankInvariant estimatorIndependence (probability theory)Mathematicsspatiaalinen merkki
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Independent component analysis based on symmetrised scatter matrices

2007

A new method for separating the mixtures of independent sources has been proposed recently in [Oja et al. (2006). Scatter matrices and independent component analysis. Austrian J. Statist., to appear]. This method is based on two scatter matrices with the so-called independence property. The corresponding method is now further examined. Simple simulation studies are used to compare the performance of so-called symmetrised scatter matrices in solving the independence component analysis problem. The results are also compared with the classical FastICA method. Finally, the theory is illustrated by some examples. peerReviewed

Statistics and ProbabilityApplied MathematicsIndependence propertyStatistical computationhajontamatriisitIndependent component analysisComputational MathematicsComputational Theory and MathematicsComponent analysisSimple (abstract algebra)CalculusSource separationFastICAApplied mathematicsICAIndependence (probability theory)MathematicsComputational Statistics & Data Analysis
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Symmetrised M-estimators of multivariate scatter

2007

AbstractIn this paper we introduce a family of symmetrised M-estimators of multivariate scatter. These are defined to be M-estimators only computed on pairwise differences of the observed multivariate data. Symmetrised Huber's M-estimator and Dümbgen's estimator serve as our examples. The influence functions of the symmetrised M-functionals are derived and the limiting distributions of the estimators are discussed in the multivariate elliptical case to consider the robustness and efficiency properties of estimators. The symmetrised M-estimators have the important independence property; they can therefore be used to find the independent components in the independent component analysis (ICA).

Statistics and ProbabilityElliptical distributionInfluence functionMultivariate statisticsNumerical AnalysisEstimatorEfficiencyM-estimatorM-estimatorIndependent component analysisEfficient estimatorScatter matrixScatter matrixMathematics::Category TheoryStatisticsApplied mathematicsStatistics Probability and UncertaintyRobustnessElliptical distributionIndependence (probability theory)MathematicsJournal of Multivariate Analysis
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Tests and estimates of shape based on spatial signs and ranks

2009

Nonparametric procedures for testing and estimation of the shape matrix in the case of multivariate elliptic distribution are considered. Testing for sphericity is an important special case. The tests and estimates are based on the spatial sign and rank covariance matrices. The estimates based on the spatial sign covariance matrix and symmetrized spatial sign covariance matrix are Tyler's [A distribution-free M-estimator of multivariate scatter, Ann. Statist. 15 (1987), pp. 234–251] shape matrix and and Dümbgen's [On Tyler's M-functional of scatter in high dimension, Ann. Inst. Statist. Math. 50 (1998), pp. 471–491] shape matrix, respectively. The test based on the spatial sign covariance m…

Statistics and ProbabilityStatistics::TheoryRank (linear algebra)Covariance matrixNonparametric statisticsCovarianceEstimation of covariance matricesScatter matrixStatisticsStatistics::MethodologySign testStatistics Probability and Uncertaintymoniulotteiset merkki- ja jarjestysluvutMathematicsSign (mathematics)Journal of Nonparametric Statistics
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Spatial sign and rank based scatter matrices with applications

2007

spatiaalinen havaitseminenavaruudellinen hahmottaminenhajontamatriisit
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