On multiple test procedures
On Seifert's ANOVA-like test for variance components
On small sample inference for common mean in heteroscedastic one-way model
In this paper we consider and compare several approximate methods for making small-sample statistical inference on the common mean in the heteroscedastic one-way random effects model. The topic of the paper was motivated by the problem of interlaboratory comparisons and is also known as the (traditional) common mean problem. It is also closely related to the problem of multicenter clinical trials and meta-analysis. Based on our simulation study we suggest to use the approach proposed by Kenward...
On some properties of ML and REML estimators in mixed normal models with two variance components
In the paper, the problem of estimation of variance components σ₁² and σ₂² by using the ML-method and REML-method in a normal mixed linear model 𝒩 {Y,E(Y) = Xβ, Cov(Y) = σ₁²V + σ₂²Iₙ} is considered. This paper deal with properties of estimators of variance components, particularly when an explicit form of these estimators is unknown. The conditions when the ML and REML estimators can be expressed in explicit forms are given, too. The simulation study for one-way classification unbalanced random...
On testing variance components in unbalanced mixed linear model
The paper presents some approximate and exact tests for testing variance components in general unbalanced mixed linear model. It extends the results presented by Seifert (1992) with emphasis on the computational aspects of the problem.
On variance of the two-stage estimator in variance-covariance components model
The paper deals with a linear model with linear variance-covariance structure, where the linear function of the parameter of expectation is to be estimated. The two-stage estimator is based on the observation of the vector and on the invariant quadratic estimator of the variance-covariance components. Under the assumption of symmetry of the distribution and existence of finite moments up to the tenth order, an approach to determining the upper bound for the difference in variances of the estimators...
On variance-covariance components estimation in linear models with AR(1) disturbances.
Optimal elimination of nuisance parameters in mixed linear models
Optimale Planung eines Kovarianzanalyse- und eines Intraclass Regressions-Experiments.
Optimale Versuchspläne bei zweifach klassifizierten Beobachtungsmodellen
Optimality of Balanced Designs for Minimum Norm Quadratic Unbiased Estimation of Variance Components.
Optimization of the size of nonsensitiveness regions
The problem is to determine the optimum size of nonsensitiveness regions for the level of statistical tests. This is closely connected with the problem of the distribution of quadratic forms.
Pointwise representation method.
Quadratic estimations in mixed linear models
In the paper four types of estimations of the linear function of the variance components are presented for the mixed linear model with expectation and covariance matrix .
Real-time parameter estimation and output prediction for ARMA-type system models
Remarks on algorithm 32
Repeated regression experiment and estimation of variance components
Robust m-estimator of parameters in variance components model
It is shown that a method of robust estimation in a two way crossed classification mixed model, recently proposed by Bednarski and Zontek (1996), can be extended to a more general case of variance components model with commutative a covariance matrices.
Robust methods in exponential smoothing
Robustness to non-normality of common tests for the many-sample location problem.