This volume comprises a comprehensive collection of original papers on the subject of estimating functions. It is intended to provide statisticians with an overview of both the theory and the applications of estimating functions in biostatistics, stochastic processes, and survey sampling. From the early 1960s when the concept of optimality criterion was first formulated, together with the later work on optimal estimating functions, this subject has become both an active research area in its own right and also a cornerstone of the modern theory of statistics. Individual chapters have been written by experts in their respective fields and as a result this volume will be an invaluable reference guide to this topic as well as providing an introduction to the area for non-experts.
"synopsis" may belong to another edition of this title.
V. P. Godambe is at University of Waterloo.
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Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9780198522287. Seller Inventory # 9740682
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First Edition. Fine copy in the original paper-covered boards. Slightest suggestion only of dust-dulling to the spine bands and panel edges. Remains particularly well-preserved overall; tight, bright, clean and strong. Physical description: xii, 344 pages ; 24 cm. Subject: Mathematics. Estimation theory. 1 Kg. Seller Inventory # 383488
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Hardcover. Condition: new. Hardcover. This volume comprises a comprehensive collection of original papers on the subject of estimating functions. It is intended to provide statisticians with an overview of both the theory and the applications of estimating functions in biostatistics, stochastic processes, and survey sampling. From the early 1960s when the concept of optimality criterion was first formulated, together with later work on optimal estimating functions, this subject has become both an activeresearch area in its own right and also a corner-stone of the modern theory of statistics.Individual chapters have been written by experts in their respective fields and as aresult this volume will be an invaluable reference guide to this topic as well as providing an introduction to the area for non-experts. Comprises a collection of papers on the subject of estimating functions, designed to provide statisticians with an overview of both theory and applications in biostatistics, stochastic processes and survey sampling. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780198522287
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1st edition. Near fine copy in the original colour-printed boards. Slight suggestion only of dust-dulling to the spine bands and panel edges. Remains particularly well-preserved overall; tight, bright, clean and strong. Physical description; xii, 344 pp., 24 cm. Notes; Includes bibliographical references and indexes. Contents; PART I: Overview -- 1. Estimating Functions: An Overview, V.P. Godambe and B.K. Kale -- Part Ii -- 2. Applications of Estimating Function Theory to Replicates of Generalized Proportional Hazards Models, I.-Shou Chang and Chao A. Hsiung -- 3. Estimating Equations for Mixed Poisson Models, C.B. Dean -- 4. Estimating Equations in Generalized Linear Models with Measurement Error, Kung-Yee Liang and Xin-Hua Liu -- 5. A Unification of Inference from Capture-Recapture Studies Through Martingale Estimating Functions, C.J. Lloyd and P. Yip -- 6. The Role of Unbiasedness in Estimating Equations, T. Yanagimoto and E. Yamamoto -- 7. Use of a Quadratic Exponential Model to Generate Estimating Equations for Means, Variances, and Covariances, L.P. Zhao and R.L. Prentice -- PART III: Stochastic Processes -- 8. Generalized Score Tests for Composite Hypotheses, I.V. Basawa -- 9. Quasi-likelihood Stochastic Processes and Optimal Estimating Functions, A.F. DesmondR -- 10. On Optimal Estimating Functions for Partially Specified Counting Process Models, P.E. Greenwood and W. Wefelmeyer -- 11. Approximate Confidence Zones in an Estimating Function Context, C.C. Heyde and Y.-X. Lin -- 12. Simplified and Two-stage Quasi-Likelihood Estimators, -- J.E. Hutton, O.T. Ogunymei and P.I. Nelson -- 13. Tests Based on an Optimal Estimate, A. Thavaneswaran -- PART IV: Survey Sampling -- 14. Estimating Functions in Survey Sampling: A Review, -- M. Ghosh -- 15. Confidence Intervals for Quantiles, V.P. Godambe -- 16. Making Use of a Regression Model for Inference About a Finite Population Mean, H. Mantel -- 17. Estimating Functions in Survey Sampling: Estimation of Superpopulation Regression Parameters, K. Vijayan -- PART V: Theory (Foundations) -- 18. Sufficiency, Ancillarity, and Information in Estimating Functions, V.P. Bhapkar -- 19. Inferential Estimation, Likelihood, and Maximum Likelihood Linear Estimating Functions, S.R. Chamberlin and D.A. Sprott -- 20. Geometrical Aspects of Efficiency Criteria for Spaces of Estimating Functions, C.G. Small and D.L. McLeish -- PART VI: Theory (General Methods) -- 21. Estimating Equations from Modified Profile Likelihood, H. Ferguson, N. Reid and D.R. Cox -- 22. Resampling Using Estimating Equations, S. Lele -- 23. On Using Bivariate Moment Equations in Mixed Normal Problems, B.G. Lindsay and P. Basak -- 24. Estimating Functions in Semi-Parametric Models, Y. Ritov. Subjects; Estimation theory. Probability, statistics, game theory. Mathematics. 1 Kg. Seller Inventory # 385870