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2012 | 49 | 1 | 1-36

Tytuł artykułu

On the General Gauss-Markov Model for Experiments in Block Designs

Treść / Zawartość

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
The main estimation and hypothesis testing results related to the Gauss- Markov model, in its general form, are recalled and the application of these results to the analysis of experiments in block designs is considered. Special attention is given to the randomization-derived model for a general block design, and for a proper block design in particular. The question whether the randomization-derived model can be considered as a particular general Gauss-Markov model is discussed. It is indicated that the former, as a mixed model, is in fact an extension of the general Gauss-Markov model. Thus, the analysis based on the randomization-derived model requires a more extended methodical approach. The present paper has been inspired by one of the last papers of Professor Wiktor Oktaba.

Wydawca

Czasopismo

Rocznik

Tom

49

Numer

1

Strony

1-36

Opis fizyczny

Daty

wydano
2012-06-01
online
2013-08-17

Twórcy

  • Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań

Bibliografia

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  • Baksalary J.K., Puntanen S. (1990): Characterizations of the best linear unbiased estimator in the general Gauss-Markov model with the use of matrix partial orderings. Linear Algebra and its Applications 127: 363-370.[Crossref]
  • Caliński T. (1996): The basic contrasts of a block design with special reference to the recovery of inter-block information. In: A. Pázman and V. Witkovský (eds.), Tatra Mountains Mathematical Publications, Vol. 7: PROBASTAT' 94 Smolenice. Mathematical Institute, Bratislava, pp. 23-37.
  • Caliński T., Kageyama S. (2000): Block Designs: A Randomization Approach, Volume I: Analysis. Lecture Notes in Statistics, Volume 150, Springer, New York.
  • Demidenko E. (2004): Mixed Models: Theory and Applications. Wiley, Hoboken, New Jersey.
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  • Gauss C.F. (1855): Méthode des Moindres Carrés. Mallet-Bachelier, Paris.
  • Houtman A.M., Speed, T.P. (2008): Balance in designed experiments with orthogonal block structure Annals of Statistics 11: 1069-1085.
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  • Jones R.M. (1959): On a property of incomplete blocks. Journal of the Royal Statistical Society, Series B 21: 172-179.
  • Kala R. (1991): Elements of the randomization theory. III. Randomization in block experiments. Listy Biometryczne|Biometrical Letters 28: 3-23 (in Polish).
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  • Neyman J. (with cooperation of K. Iwaszkiewicz and S. Ko lodziejczyk) (1935): Statistical problems in agricultural experimentation (with discussion). Journal of the Royal Statistical Society, Supplement 2: 107-180.
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  • Oktaba W. (1984): Tests of hypotheses for the general Gauss-Markov model. Biometrical Journal 26: 415-424.[Crossref]
  • Oktaba W. (1989): F-tests for hypotheses with block matrices and under conditions of orthogonality in the general multivariate Gauss-Markov model. Biometrical Journal 31: 317-323.[Crossref]
  • Oktaba W. (1996): Asymptotically normal distributions in the multivariate Gauss- Markov model. Listy Biometryczne|Biometrical letters 33: 25-31.
  • Oktaba W. (1998): Characterization of the multivariate Gauss-Markov model with singular covariance matrix. Applications of Mathematics 43: 119-131.[Crossref]
  • Oktaba W. (2003): The general multivariate Gauss-Markov model of the incomplete block design. Australian & New Zealand Journal of Statistics 45: 195-205.[Crossref]
  • Oktaba W., Kornacki A., Wawrzosek J. (1986): Estimation of missing values in the general Gauss-Markov model. Statistics 17: 167-177.[Crossref]
  • Oktaba W., Kornacki A., Wawrzosek J. (1988): Invariant linearly suficient transformations of the general Gauss-Marko model. Estimation and testing. Scandinavian Journal of Statistics 17: 117-124.
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Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.doi-10_2478_bile-2013-0001
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