# Quasi-Likelihood And Its Application: A General Approach to Optimal Parameter Estimation (Springer Series in Statistics) ebook

## by Christopher C. Heyde

Christopher C. Heyde.

Christopher C. Quasi-likelihood is a very generally applicable estimating function based methodology for optimally estimating model parameters in systems subject to random effects. Only assumptions about means and covariances are required in contrast to the full distributional assumptions of ordinary likelihood based methodology.

This book is concerned with the general theory of optimal estimation of - rameters in. .Springer Series in Statistics. Bibliographic Information. Quasi-Likelihood And Its Application.

This book is concerned with the general theory of optimal estimation of - rameters in systems subject to random e?ects and with the application of this theory. The focus is on choice of families of estimating functions, rather than the estimators derived therefrom, and on optimization within these. A General Approach to Optimal Parameter Estimation. Heyde Series: Springer Series in Statistics. Series: Springer Series in Statistics.

by Christopher C. Heyde (Author). From the Inside Flap. The powerful message of this timely book is that 'for estimation of parameters in stochastic systems of any kind. There is often little, if any, loss in efficiency. Chris Heyde has played a major role in the development of QLE. Much of the work in this wonderful book can be traced directly or indirectly to his ideas.

Quasi-Likelihood And Its Application: A General Approach to Optimal Parameter

Quasi-Likelihood And Its Application: A General Approach to Optimal Parameter. Christopher C. This book is concerned with the general theory of optimal estimation of pa-rameters in systems subject to random eects and with the application of this theory. The focus is on choice of families of estimating functions, rather than the estimators derived therefrom, and on optimization within these families.

Springer Series in Statistics Advisors: P. Bickel, P. Diggle, S. Fienberg, U. Gather, I. Olkin, S. Zeger . Zeger The French e.Permutation Methods: A Distance Function Approach (Springer Series in Statistics) Permutation Methods: A Distance Function Approach (Springer Series in Statistics). A Comparison of the Bayesian and Frequentist Approaches to Estimation (Springer Series in Statistics).

Springer Series in Statistics.

Title: Springer series in statistics. Bibliography, etc. Note: Includes bibliographical references (p. -226) and index

Title: Springer series in statistics. -226) and index. Rubrics: Parameter estimation. ISBN: 8470304070 Author: Vaca de Osma, José Antonio. Publication & Distribution: Madrid. Biblioteca Nueva, (c)1996. Download book Quasi-likelihood and its application : a general approach to optimal parameter estimation, Christopher C.

Quasi-Likelihood and Its Application: A General Approach to Optimal Parameter Estimation

Quasi-Likelihood and Its Application: A General Approach to Optimal Parameter Estimation. In this paper, an extension to the more general case where the coefficients of an AR(1) model is a random variable and the error sequence is a sequence of martingale differences is discussed. A conditional least squares estimator of the autoregressive coefficient is derived and shown to be asymptotically normal.

Quasi-likelihood and its application: a general approach to optimal parameter estimation. Читать книгу бесплатно. Скачать книгу с нашего сайта нельзя. The treatment is rather informal, emphasizing essential princples rather than detailed proofs. Many examples of the use of the methods in both classical statistical and stochastic process contexts are provided.