Testing hypotheses in universal models

• Autorzy: Eva Fišerová
• Języki publikacji: EN

Abstrakty

EN

A linear regression model, when a design matrix has not full column rank and a covariance matrix is singular, is considered. The problem of testing hypotheses on mean value parameters is studied. Conditions when a hypothesis can be tested or when need not be tested are given. Explicit forms of test statistics based on residual sums of squares are presented.

Słowa kluczowe

EN

universal linear model; unbiased estimator; tests hypotheses

Kategorie tematyczne

• 62J05: Linear regression
• 62F03: Hypothesis testing
• 62F10: Point estimation

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2006
• Tom: 26
• Numer: 2
• Strony: 127-149

Daty

wydano

2006

otrzymano

2006-01-11

Twórcy

autor

Eva Fišerová

• Department of Mathematical Analysis and Applied Mathematics Faculty of Science, Palacký University Tomkova 40, 779 00 Olomouc, Czech Republic

Bibliografia

• [1] L. Kubáček, L. Kubáčková and J. Volaufová, Statistical models with linear structures, Veda, Bratislava 1995.
• [2] P.B. Pantnaik, The non-central χ² and F-distribution and their applications, Biometrika 36 (1949), 202-232.
• [3] C.R. Rao, Linear statistical inference and its applications, J. Wiley and Sons, New York-London-Sydney 1965.
• [4] C.R. Rao and S.K. Mitra, Generalized inverse of matrices and its applications, J. Wiley and Sons, New York-London-Sydney-Toronto 1971.
• [5] J. Ryšavý, Higher geodesy, Česká matice technická, Praha 1947 (in Czech).

Identyfikatory

DOI

10.7151/dmps.1078