Estimating Functions PDF Download
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Author | : Parimal Mukhopadhyay |
Publisher | : Alpha Science Int'l Ltd. |
Total Pages | : 252 |
Release | : 2004 |
Genre | : Business & Economics |
ISBN | : 9781842651636 |
Download An Introduction to Estimating Functions Book in PDF, ePub and Kindle
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.
Author | : Ishwar V. Basawa |
Publisher | : IMS |
Total Pages | : 460 |
Release | : 1997 |
Genre | : Mathematics |
ISBN | : 9780940600447 |
Download Selected Proceedings of the Symposium on Estimating Functions Book in PDF, ePub and Kindle
Author | : Christopher G. Small |
Publisher | : Oxford University Press |
Total Pages | : 330 |
Release | : 2003 |
Genre | : Mathematics |
ISBN | : 9780198506881 |
Download Numerical Methods for Nonlinear Estimating Equations Book in PDF, ePub and Kindle
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.
Author | : V. P. Godambe |
Publisher | : Oxford University Press on Demand |
Total Pages | : 344 |
Release | : 1991 |
Genre | : History |
ISBN | : 9780198522287 |
Download Estimating Functions Book in PDF, ePub and Kindle
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.
Author | : Andreas Ziegler |
Publisher | : Springer Science & Business Media |
Total Pages | : 155 |
Release | : 2011-06-17 |
Genre | : Mathematics |
ISBN | : 1461404991 |
Download Generalized Estimating Equations Book in PDF, ePub and Kindle
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.
Author | : James W. Hardin |
Publisher | : CRC Press |
Total Pages | : 277 |
Release | : 2012-12-10 |
Genre | : Mathematics |
ISBN | : 1439881146 |
Download Generalized Estimating Equations Book in PDF, ePub and Kindle
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
Author | : V. P. Godambe |
Publisher | : |
Total Pages | : 344 |
Release | : 1991 |
Genre | : Estimation theory |
ISBN | : |
Download Estimating Functions Book in PDF, ePub and Kindle
Author | : Shun-ichi Amari |
Publisher | : American Mathematical Soc. |
Total Pages | : 220 |
Release | : 2000 |
Genre | : Computers |
ISBN | : 9780821843024 |
Download Methods of Information Geometry Book in PDF, ePub and Kindle
Information geometry provides the mathematical sciences with a fresh framework of analysis. This book presents a comprehensive introduction to the mathematical foundation of information geometry. It provides an overview of many areas of applications, such as statistics, linear systems, information theory, quantum mechanics, and convex analysis.
Author | : Christopher G. Small |
Publisher | : Oxford University Press |
Total Pages | : 322 |
Release | : 2003 |
Genre | : Mathematics |
ISBN | : 0198506880 |
Download Numerical Methods for Nonlinear Estimating Equations Book in PDF, ePub and Kindle
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.
Author | : James W. Hardin |
Publisher | : CRC Press |
Total Pages | : 237 |
Release | : 2002-07-30 |
Genre | : Mathematics |
ISBN | : 1420035282 |
Download Generalized Estimating Equations Book in PDF, ePub and Kindle
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