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1978•Communication in Statistics- Theory and MethodsRequires access

Maximum likelihood analysis of the mixed model: the balanced case

David W. Smith, Ronald Raymond Hocking

Open publisher page 16 citations

Abstract

The primary purpose of this paper is to develop, analytically, the inverse of the covariance matrix for the mixed analysis-of-variance model with balanced data. The use of this matrix in the identification of minimal sufficient statistics and in developing the likelihood equations is illustrated.

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What this paper is about

The primary purpose of this paper is to develop, analytically, the inverse of the covariance matrix for the mixed analysis-of-variance model with balanced data. The use of this matrix in the identification of minimal sufficient statistics and in developing the likelihood equations is illustrated.

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OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The primary purpose of this paper is to develop, analytically, the inverse of the covariance matrix for the mixed analysis-of-variance model with balanced data. The use of this matrix in the identification of minimal sufficient statistics and in developing the likelihood equations is illustrated.

Key concepts: Statistics, Mathematics, Restricted maximum likelihood, Identification (biology), Inverse, Maximum likelihood, Applied mathematics, Covariance matrix

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