Name: Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (en Inglés)
SKU: 7585430
Price: 198840.00 CLP
Availability: InStock
Author: Silvapulle, Mervyn J. ; Sen, Pranab Kumar
ISBN: 9780471208273

portada Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (en Inglés)

Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (en Inglés)

Formato

Libro Físico

Autor

Mervyn J. Silvapulle

Pranab Kumar Sen

Editorial

Wiley-Interscience

Idioma

Inglés

N° páginas

532

Encuadernación

Tapa Dura

Dimensiones

24.3x16.4x3 cm

Peso

0.90 kg.

ISBN

471208272

ISBN13

9780471208273

N° edición

Categorías

Probabilidad y estadística

Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (en Inglés)

Mervyn J. Silvapulle (Autor) · Pranab Kumar Sen (Autor) · Wiley-Interscience · Tapa Dura

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Reseña del libro "Constrained Statistical Inference: Inequality, Order, and Shape Restrictions (en Inglés)"

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