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Linear Processes in Function Spaces

Theory and Applications

  • Denis Bosq

Part of the Lecture Notes in Statistics book series (LNS, volume 149)

Table of contents

About this book

Introduction

The main subject of this book is the estimation and forecasting of continuous time processes. It leads to a development of the theory of linear processes in function spaces.
The necessary mathematical tools are presented in Chapters 1 and 2. Chapters 3 to 6 deal with autoregressive processes in Hilbert and Banach spaces. Chapter 7 is devoted to general linear processes and Chapter 8 with statistical prediction. Implementation and numerical applications appear in Chapter 9. The book assumes a knowledge of classical probability theory and statistics. Denis Bosq is Professor of Statistics at the University of Paris 6 (Pierre et Marie Curie). He is Chief-Editor of Statistical Inference for Stochastic Processes and of Annales de l'ISUP, and Associate Editor of the Journal of Nonparametric Statistics. He is an elected member of the International Statistical Institute, and he has published about 100 papers or works on nonparametric statistics and five books including Nonparametric Statistics for Stochastic Processes: Estimation and Prediction, Second Edition (Springer, 1998).

Keywords

Distribution Hilbert space Parametric statistics Probability theory Random variable Variance correlation

Authors and affiliations

  • Denis Bosq
    • 1
  1. 1.Institut de StatistiqueUniversité Pierre et Marie CurieParis Cedex 05France

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1154-9
  • Copyright Information Springer-Verlag New York, Inc. 2000
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-95052-5
  • Online ISBN 978-1-4612-1154-9
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site