Multivariate Time Series With Linear State Space Structure / by Víctor Gómez.

Format:

Book

Author/Creator:

Gómez, Víctor, Author.

Language:

English

Subjects (All):

Statistics.

Mathematical statistics--Data processing.

Mathematical statistics.

Probabilities.

Econometrics.

Statistical Theory and Methods.

Statistics and Computing.

Probability Theory.

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Statistics in Business, Management, Economics, Finance, Insurance.

Local Subjects:

Statistical Theory and Methods.

Statistics and Computing.

Probability Theory.

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Econometrics.

Statistics in Business, Management, Economics, Finance, Insurance.

Physical Description:

1 online resource (553 p.)

Edition:

1st ed. 2016.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

Summary:

This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intendedfor researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.

Contents:

Preface

Computer Software

Orthogonal Projection

Linear Models

Stationarity and Linear Time Series Models

The State Space Model

Time Invariant State Space Models

Time Invariant State Space Models With Inputs

Wiener–Kolmogorov Filtering and Smoothing

SSMMATLAB

Bibliography

Author Index

Subject Index.

Notes:

Description based upon print version of record.

Includes bibliographical references and indexes.

ISBN:

3-319-28599-8