Geodesic
Outliers in models with constraints
Kybernetika, Tome 42 (2006) no. 6, pp. 673-698 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

Voir la notice de l'article

Outliers in univariate and multivariate regression models with constraints are under consideration. The covariance matrix is assumed either to be known or to be known only partially.
Outliers in univariate and multivariate regression models with constraints are under consideration. The covariance matrix is assumed either to be known or to be known only partially.
Classification : 62F10, 62F30, 62F35, 62H12, 62J05, 62J20
Keywords: univariate regression model; multivariate regression model; constraints; outlier; variance components 
@article{KYB_2006_42_6_a3,
     author = {Kub\'a\v{c}ek, Lubom{\'\i}r},
     title = {Outliers in models with constraints},
     journal = {Kybernetika},
     pages = {673--698},
     year = {2006},
     volume = {42},
     number = {6},
     mrnumber = {2296508},
     zbl = {1249.62005},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_2006_42_6_a3/}
}
TY  - JOUR
AU  - Kubáček, Lubomír
TI  - Outliers in models with constraints
JO  - Kybernetika
PY  - 2006
SP  - 673
EP  - 698
VL  - 42
IS  - 6
UR  - http://geodesic.mathdoc.fr/item/KYB_2006_42_6_a3/
LA  - en
ID  - KYB_2006_42_6_a3
ER  - 
%0 Journal Article
%A Kubáček, Lubomír
%T Outliers in models with constraints
%J Kybernetika
%D 2006
%P 673-698
%V 42
%N 6
%U http://geodesic.mathdoc.fr/item/KYB_2006_42_6_a3/
%G en
%F KYB_2006_42_6_a3
Kubáček, Lubomír. Outliers in models with constraints. Kybernetika, Tome 42 (2006) no. 6, pp. 673-698. http://geodesic.mathdoc.fr/item/KYB_2006_42_6_a3/

[1] Anderson T. W.: Introduction to Multivariate Statistical Analysis. Wiley, New York 1958 | MR | Zbl

[2] Barnett V., Lewis T.: Outliers in Statistical Data. Wiley, New York 1994 | MR | Zbl

[3] Gnanadesikan R.: Methods for Statistical Data Analysis of Multivariate Observations. Wiley, New York – Chichester – Weinheim – Brisbane – Singapore – Toronto 1997 | MR | Zbl

[4] Humak K. M. S.: Statistische Methoden der Modellbildung, Band I. Akademie Verlag, Berlin 1977 | MR | Zbl

[5] Kubáček L., Kubáčková, L., Volaufová J.: Statistical Models with Linear Structures. Veda, Bratislava 1995

[6] Kubáček L., Kubáčková L.: Nonsensitiveness regions in universal models. Math. Slovaca 50 (2000), 219–240 | MR | Zbl

[7] Lešanská E.: Insensitivity regions in mixed models (in Czech). Ph.D. Thesis. Faculty of Science, Palacký University, Olomouc 2001

[8] Lešanská E.: Insensitivity regions for testing hypotheses in mixed models with constraints. Tatra Mt. Math. Publ. 22 (2001), 209–222 | MR | Zbl

[9] Lešanská E.: Optimization of the size of nonsensitivity regions. Appl. Math. 47 (2002), 9–23 | DOI | MR

[10] Rao C. R., Mitra S. K.: Generalized Inverse of Matrices and Its Applications. Wiley, New York 1971 | MR | Zbl

[11] Rao C. R., Kleffe J.: Estimation of Variance Components and Applications. North–Holland, Amsterdam 1988 | MR | Zbl

[12] Scheffé H.: The Analysis of Variance. Wiley, New York 1959 | MR | Zbl

[13] Zvára K.: Regression Analysis (in Czech). Academia, Praha 1989