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Author: Parimal Mukhopadhyay Publisher: Alpha Science Int'l Ltd. ISBN: 9781842651636 Category : Business & Economics Languages : en Pages : 252
Book Description
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: Parimal Mukhopadhyay Publisher: Alpha Science Int'l Ltd. ISBN: 9781842651636 Category : Business & Economics Languages : en Pages : 252
Book Description
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: Christopher G. Small Publisher: Oxford University Press ISBN: 9780198506881 Category : Mathematics Languages : en Pages : 330
Book Description
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: Anil K. Bera Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The idea of using estimating functions goes a long way back, at least to Karl Pearson's introduction to the method of moment in 1894. It is now a very active area of research in the statistics literature. One aim of this chapter is to provide an account of the developments relating to the theory of estimating functions. Starting from the simple case of single parameter under independent set up, we cover the multi-parameter, presence of nuisance parameters and dependent data cases. Applications of the estimating function technique to econometrics is still at its infancy. However, we illustrate how this estimation approach could be used in various time series models, such as random coefficient, threshold, bilinear, autoregressive conditional heteroscedasticity models, also in spatial, longitudinal data and median regression analyses. The chapter is concluded with some remarks on the place of estimating function in the history of the statistical estimation techniques.
Author: James W. Hardin Publisher: CRC Press ISBN: 1439881146 Category : Mathematics Languages : en Pages : 277
Book Description
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: Andreas Ziegler Publisher: Springer Science & Business Media ISBN: 1461404991 Category : Mathematics Languages : en Pages : 155
Book Description
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: Cohen Publisher: CRC Press ISBN: 9780824779801 Category : Mathematics Languages : en Pages : 422
Book Description
Offers an applications-oriented treatment of parameter estimation from both complete and censored samples; contains notations, simplified formats for estimates, graphical techniques, and numerous tables and charts allowing users to calculate estimates and analyze sample data quickly and easily. Anno
Author: Jaya P. N. Bishwal Publisher: Springer ISBN: 3540744487 Category : Mathematics Languages : en Pages : 271
Book Description
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
Author: Parimal Mukhopadhyay
Author: Parimal Mukhopadhyay
Author: Christopher G. Small
Author: Anil K. Bera
Author: James W. Hardin
Author: Ishwar V. Basawa
Author: Andreas Ziegler
Author: Cohen
Author: 
Author: V. P. Godambe
Author: Jaya P. N. Bishwal