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Robust estimation in the multivariate normal model

100%

Kulawik A., Zontek S.

Discussiones Mathematicae Probability and Statistics

2016

tom 36

nr 1-2

53-66

Robust estimation presented in the following paper is based on Fisher consistent and Fréchet differentiable statistical functionals. The method has been used in the multivariate normal model with variance components [5]. To transfer the method to estimate vector of expectations and positive definite covariance matrix of the multivariate normal model it is required to express the covariance matrix as a linear combination of basic elements of the vector space of real, square and symmetric matrices. The theoretical results have been completed with computer simulation studies. The robust estimator has been investigated both for model and contaminated data. Comparison with the maximum likelihood estimator has also been included.

Robust m-estimator of parameters in variance components model

100%

Zmyślony R., Zontek S.

Discussiones Mathematicae Probability and Statistics

2002

tom 22

nr 1-2

61-71

It is shown that a method of robust estimation in a two way crossed classification mixed model, recently proposed by Bednarski and Zontek (1996), can be extended to a more general case of variance components model with commutative a covariance matrices.

Ograniczanie wyników

2 Discussiones Mathematicae Probability and Statistics

2 Zontek S.

1 Kulawik A.

1 Zmyślony R.

1 2016

1 2002

Wyniki wyszukiwania

Robust estimation in the multivariate normal model

Robust m-estimator of parameters in variance components model