Algorithm AS 225: Minimizing Linear Inequality Constrained Mahalanobis Distances

DOI10.2307/2347557zbMath0617.62082OpenAlexW2519033097MaRDI QIDQ4727231

P. C. Wollan, Richard L. Dykstra

Publication date: 1987

Published in: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/2347557

zbMATH Keywords

linear inequality constraintsMahalanobis distanceKuhn-Tucker vectorsFortran 66algorithm AS 225

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Linear regression; mixed models (62J05) Linear inference, regression (62J99)

Related Items (12)

Estimating and testing generalized linear models under inequality restrictions ⋮ ROBUST TESTS FOR THE SIGNIFICANCE OF ORTHANT RESTRICTED MEAN VECTOR ⋮ Some improved tests for multivariate one-sided hypotheses ⋮ Probabilistic-statistical programs from ``Applied Statistics ⋮ A cone order monotone test for the one-sided multivariate testing problem. ⋮ The restricted EM algorithm under inequality restrictions on the parameters ⋮ Testing for one-sided group effects in repeated measures study ⋮ One-Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations ⋮ A conditional test for a non-negative mean vector based on a Hotelling's \(T^2\)-type statistic ⋮ AS 225 ⋮ Extension of the pool-adjacent-violators algorithm ⋮ An appraisal of some aspects of statistical inference under inequality constraints

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