silvapulle (7 Ergebnisse)

Zustand: Good. Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In.

Gebunden. Zustand: New. MERVYN J. SILVAPULLE, PhD, is an Associate Professor in the Department of Statistical Science at La Trobe University in Bundoora, Australia. He received his PhD in statistics from the Australian National University in 1981.PRANAB K. SEN, PhD, is a Professor.

Hardcover. Zustand: Brand New. 1st edition. 532 pages. 9.25x6.25x1.25 inches. In Stock.

Zustand: New. An up-to-date approach to understanding statistical inference Statistical inference is finding useful applications in numerous fields, from sociology and econometrics to biostatistics. Series: Wiley Series in Probability and Statistics. Num Pages: 532 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 242 x 161 x 31. Weight in Grams: 896. . 2004. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - An up-to-date approach to understanding statistical inferenceStatistical inference is finding useful applications in numerous fields, from sociology and econometrics to biostatistics. This volume enables professionals in these and related fields to master the concepts of statistical inference under inequality constraints and to apply the theory to problems in a variety of areas.Constrained Statistical Inference: Order, Inequality, and Shape Constraints provides a unified and up-to-date treatment of the methodology. It clearly illustrates concepts with practical examples from a variety of fields, focusing on sociology, econometrics, and biostatistics.The authors also discuss a broad range of other inequality-constrained inference problems that do not fit well in the contemplated unified framework, providing a meaningful way for readers 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 density function, shape constraints, and DMRL functionsBayesian perspectives, including Stein's Paradox, shrinkage estimation, and decision theory.