Exponential Families of Stochastic Processes (Springer Series in Statistics)

Küchler, Uwe; Sorensen, Michael

ISBN 10: 038794981X / ISBN 13: 9780387949819

Published by Springer (edition 1997), 1997

About this Item

It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Seller Inventory # 038794981X-8-1

Bibliographic Details

• Title: Exponential Families of Stochastic Processes (Springer Series in Statistics)
• Publisher: Springer (edition 1997)
• Publication Date: 1997
• Language: English
• ISBN 10: 038794981X
• ISBN 13: 9780387949819
• Binding: Hardcover
• Edition: 1997.
• Condition: Very Good

About this title

Synopsis

Exponential families of stochastic processes are parametric stochastic p- cess models for which the likelihood function exists at all ?nite times and has an exponential representation where the dimension of the canonical statistic is ?nite and independent of time. This de?nition not only covers manypracticallyimportantstochasticprocessmodels,italsogivesrisetoa rather rich theory. This book aims at showing both aspects of exponential families of stochastic processes. Exponential families of stochastic processes are tractable from an a- lytical as well as a probabilistic point of view. Therefore, and because the theory covers many important models, they form a good starting point for an investigation of the statistics of stochastic processes and cast interesting light on basic inference problems for stochastic processes. Exponential models play a central role in classical statistical theory for independent observations, where it has often turned out to be informative and advantageous to view statistical problems from the general perspective of exponential families rather than studying individually speci?c expon- tial families of probability distributions. The same is true of stochastic process models. Thus several published results on the statistics of parti- lar process models can be presented in a uni?ed way within the framework of exponential families of stochastic processes.