6533b850fe1ef96bd12a8215

RESEARCH PRODUCT

Linear and ellipsoidal restrictions in linear regression

P. StahleckerGötz Trenkler

subject

Statistics and ProbabilityPolynomial regressionStatistics::TheoryMathematical optimizationProper linear modelLinear predictor functionBayesian multivariate linear regressionLinear regressionLinear modelPrincipal component regressionStatistics Probability and UncertaintySimple linear regressionMathematics

description

The problem of combining linear and ellipsoidal restrictions in linear regression is investigated. Necessary and sufficient conditions for compactness of the restriction set are proved assuring the existence of a minimax estimator. When the restriction set is not compact a minimax estimator may still exist for special loss functions arid regression designs

yearjournalcountryeditionlanguage
1991-01-01Statistics
https://doi.org/10.1080/03610929108802299