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Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (in English)
Mervyn J. Silvapulle
(Author)
·
Pranab Kumar Sen
(Author)
·
Wiley-Interscience
· Hardcover
Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (in English) - Silvapulle, Mervyn J. ; Sen, Pranab Kumar
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Synopsis "Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (in English)"
An up-to-date approach to understanding statistical inference Statistical inference is finding useful applications in numerousfields, from sociology and econometrics to biostatistics. Thisvolume enables professionals in these and related fields to masterthe concepts of statistical inference under inequality constraintsand to apply the theory to problems in a variety of areas.Constrained Statistical Inference: Order, Inequality, and ShapeConstraints provides a unified and up-to-date treatment of themethodology. It clearly illustrates concepts with practicalexamples from a variety of fields, focusing on sociology,econometrics, and biostatistics.The authors also discuss a broad range of otherinequality-constrained inference problems that do not fit well inthe contemplated unified framework, providing a meaningful way forreaders to comprehend methodological resolutions.Chapter coverage includes:Population means and isotonic regressionInequality-constrained tests on normal meansTests in general parametric modelsLikelihood and alternativesAnalysis of categorical dataInference on monotone density function, unimodal densityfunction, shape constraints, and DMRL functionsBayesian perspectives, including Stein’s Paradox,shrinkage estimation, and decision theory
