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Isotonic regression for metallic microstructure data: estimation and testing under order restrictions

2021

Investigating the main determinants of the mechanical performance of metals is not a simple task. Already known physical inspired qualitative relations between 2D microstructure characteristics and 3D mechanical properties can act as the starting point of the investigation. Isotonic regression allows to take into account ordering relations and leads to more efficient and accurate results when the underlying assumptions actually hold. The main goal in this paper is to test order relations in a model inspired by a materials science application. The statistical estimation procedure is described considering three different scenarios according to the knowledge of the variances: known variance ra…

FOS: Computer and information sciencesStatistics and ProbabilityMathematical optimizationgeometrically necessary dislocationsComputer science0211 other engineering and technologiesG.302 engineering and technology01 natural sciencesStatistics - ApplicationsMethodology (stat.ME)010104 statistics & probabilitySimple (abstract algebra)Isotonic regressionApplications (stat.AP)0101 mathematicsbootstraporder restrictionsStatistics - Methodology021103 operations researchlikelihood ratio testMicrostructurealternating iterative methodOrder (business)Geometrically necessary dislocationsLikelihood-ratio testStatistics Probability and UncertaintyIsotonic regression62F30 62F03 97K80
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