Non-Standard Parametric Statistical Inference
Author:   Russell C. H. Cheng (, University of Southampton)
Publisher:   Oxford University Press
ISBN:  

9780198505044


Pages:   430
Publication Date:   22 June 2017
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Non-Standard Parametric Statistical Inference


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Author:   Russell C. H. Cheng (, University of Southampton)
Publisher:   Oxford University Press
Imprint:   Oxford University Press
Dimensions:   Width: 17.30cm , Height: 2.90cm , Length: 23.50cm
Weight:   0.848kg
ISBN:  

9780198505044


ISBN 10:   0198505043
Pages:   430
Publication Date:   22 June 2017
Audience:   College/higher education ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1: Introduction 2: Non-Standard Problems: Some Examples 3: Standard Asymptotic Theory 4: Bootstrap Analysis 5: Embedded Model Problem 6: Examples of Embedded Distributions 7: Embedded Distributions: Two Numerical Examples 8: Infinite Likelihood 9: The Pearson and Johnson Systems 10: Box-Cox Transformations 11: Change-Point Models 12: The Skew Normal Distribution 13: Randomized-Parameter Models 14: Indeterminacy 15: Nested Nonlinear Regression Models 16: Bootstrapping Linear Models 17: Finite Mixture Models 18: Finite Mixture Examples: MAPIS Details

Reviews

This book will be of interest for practitioners, and might be used as an advanced undergraduate or introductory graduate textbook for a course in applied statistics and/or econometrics. * Gilles Teyssiere, MathSciNet *


Author Information

Russell Cheng is Emeritus Professor of Operational Research at the University of Southampton. He has an M.A. and a Diploma in Mathematical Statistics from Cambridge University, and obtained his Ph.D. from Bath University. He is a former Chairman of the U.K. Simulation Society, a former Fellow of the Royal Statistical Society, and Fellow of the Institute of Mathematics and Its Applications. His research interests include: design and analysis of simulation experiments and parametric estimation methods. He founded and was Joint Editor of the IMA Journal of Management Mathematics.

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