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An Introduction to Estimating Functions

An Introduction to Estimating Functions
Author: Parimal Mukhopadhyay
Publisher: Alpha Science Int'l Ltd.
Total Pages: 252
Release: 2004
Genre: Business & Economics
ISBN: 9781842651636

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The theory of estimating functions plays a major role in analysis of data pertaining to Biostatistics, Econometrics, Time Series Analysis, Reliability studies and other varied fields. This book discusses at length the application of the theory in interpretation of results in Survey Sampling.


Numerical Methods for Nonlinear Estimating Equations

Numerical Methods for Nonlinear Estimating Equations
Author: Christopher G. Small
Publisher: Oxford University Press
Total Pages: 330
Release: 2003
Genre: Mathematics
ISBN: 9780198506881

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Non linearity arises in statistical inference in various ways, with varying degrees of severity, as an obstacle to statistical analysis. More entrenched forms of nonlinearity often require intensive numerical methods to construct estimators, and the use of root search algorithms, or one-step estimators, is a standard method of solution. This book provides a comprehensive study of nonlinear estimating equations and artificial likelihood's for statistical inference. It provides extensive coverage and comparison of hill climbing algorithms, which when started at points of nonconcavity often have very poor convergence properties, and for additional flexibility proposes a number of modification to the standard methods for solving these algorithms. The book also extends beyond simple root search algorithms to include a discussion of the testing of roots for consistency, and the modification of available estimating functions to provide greater stability in inference. A variety of examples from practical applications are included to illustrate the problems and possibilities thus making this text ideal for the research statistician and graduate student.


Estimating Functions

Estimating Functions
Author: V. P. Godambe
Publisher: Oxford University Press on Demand
Total Pages: 344
Release: 1991
Genre: History
ISBN: 9780198522287

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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.


Generalized Estimating Equations

Generalized Estimating Equations
Author: James W. Hardin
Publisher: CRC Press
Total Pages: 277
Release: 2012-12-10
Genre: Mathematics
ISBN: 1439881146

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Generalized Estimating Equations, Second Edition updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, al


Generalized Estimating Equations

Generalized Estimating Equations
Author: Andreas Ziegler
Publisher: Springer Science & Business Media
Total Pages: 155
Release: 2011-06-17
Genre: Mathematics
ISBN: 1461404991

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Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too restrictive for many problems. Therefore, the main goal of this book is to give a systematic presentation of the original generalized estimating equations (GEE) and some of its further developments. Subsequently, the emphasis is put on the unification of various GEE approaches. This is done by the use of two different estimation techniques, the pseudo maximum likelihood (PML) method and the generalized method of moments (GMM). The author details the statistical foundation of the GEE approach using more general estimation techniques. The book could therefore be used as basis for a course to graduate students in statistics, biostatistics, or econometrics, and will be useful to practitioners in the same fields.


Estimating Functions

Estimating Functions
Author: V. P. Godambe
Publisher:
Total Pages: 344
Release: 1991
Genre: Estimation theory
ISBN:

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Generalized Estimating Equations

Generalized Estimating Equations
Author: James W. Hardin
Publisher: CRC Press
Total Pages: 237
Release: 2002-07-30
Genre: Mathematics
ISBN: 1420035282

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Although powerful and flexible, the method of generalized linear models (GLM) is limited in its ability to accurately deal with longitudinal and clustered data. Developed specifically to accommodate these data types, the method of Generalized Estimating Equations (GEE) extends the GLM algorithm to accommodate the correlated data encountered in heal


Generalized Estimating Equations, Second Edition

Generalized Estimating Equations, Second Edition
Author: James W. Hardin
Publisher: CRC Press
Total Pages: 280
Release: 2012-12-10
Genre: Mathematics
ISBN: 1439881138

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Generalized Estimating Equations, Second Edition updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, along with the software code used to create, run, and evaluate the models being examined. Stata is used as the primary software for running and displaying modeling output; associated R code is also given to allow R users to replicate Stata examples. Specific examples of SAS usage are provided in the final chapter as well as on the book’s website. This second edition incorporates comments and suggestions from a variety of sources, including the Statistics.com course on longitudinal and panel models taught by the authors. Other enhancements include an examination of GEE marginal effects; a more thorough presentation of hypothesis testing and diagnostics, covering competing hierarchical models; and a more detailed examination of previously discussed subjects. Along with doubling the number of end-of-chapter exercises, this edition expands discussion of various models associated with GEE, such as penalized GEE, cumulative and multinomial GEE, survey GEE, and quasi-least squares regression. It also offers a thoroughly new presentation of model selection procedures, including the introduction of an extension to the QIC measure that is applicable for choosing among working correlation structures. See Professor Hilbe discuss the book.