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On eliminating transformations for nuisance parameters in multivariate linear model

Pavla Kunderová (2004)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

The multivariate linear model, in which the matrix of the first order parameters is divided into two matrices: to the matrix of the useful parameters and to the matrix of the nuisance parameters, is considered. We examine eliminating transformations which eliminate the nuisance parameters without loss of information on the useful parameters and on the variance components.

On spectral properties of linear combinations of idempotents

Hong-Ke Du, Chun-Yan Deng, Mostafa Mbekhta, Vladimír Müller (2007)

Studia Mathematica

Let P,Q be two linear idempotents on a Banach space. We show that the closedness of the range and complementarity of the kernel (range) of linear combinations of P and Q are independent of the choice of coefficients. This generalizes known results and shows that many spectral properties of linear combinations do not depend on their coefficients.

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