Stochastic ordering and Schur-convex functions in comparison of linear experiments

DOI10.1007/BF02614102zbMath0692.62006OpenAlexW2013313608MaRDI QIDQ583752

Czesław Stȩpniak

Publication date: 1989

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/176244

zbMATH Keywords

design of experimentsstochastic orderingSchur-convex functions1-way random modelnormality assumptionordering of linear experimentsquadratic risk of attainable linear estimatorsrisk-freestochastic precision

Mathematics Subject Classification ID

Theory of statistical experiments (62B15)

Related Items (16)

Comparison of experiments via a group majorization ordering ⋮ The Schur multiplicative and harmonic convexities of the complete symmetric function ⋮ Some properties of a class of symmetric functions and its applications ⋮ Sandwich theorem in comparison of multivariate normal experiments ⋮ Quotient of information matrices in comparison of linear experiments for quadratic estimation ⋮ Schur convexity for two classes of symmetric functions and their applications ⋮ The Schur multiplicative and harmonic convexities for three classes of symmetric functions ⋮ Comparing Normal Linear Experiments and Transformation of Observations * ⋮ Some properties for a class of symmetric functions with applications ⋮ Schur-convexity for a class of symmetric functions and its applications ⋮ Schur convexity for a class of symmetric functions ⋮ Convexity of the integral arithmetic mean of a convex function ⋮ Ordering of transformed recorded electroencephalography (EEG) signals by a novel precede operator ⋮ Shape optimal design criterion in linear models ⋮ The Schur harmonic convexity of the Hamy symmetric function and its applications ⋮ Solution of an open problem for Schur convexity or concavity of the Gini mean values

Cites Work

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• Orderings of linear models
• Comparison of linear experiments with known covariances
• Optimal allocation of units in experimental designs with hierarchical and cross classification
• Universal domination and stochastic domination: Estimation simultaneously under a broad class of loss functions
• Group invariant orderings and experimental designs
• Reduction problems in comparison of linear models
• Comparing location experiments
• Optimal allocation of observations in one-way random normal model
• Linear Statistical Inference and its Applications
• Equivalent Comparisons of Experiments
• Ordered Families of Distributions
• Inequalities: theory of majorization and its applications

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