Text

Multivariate Time Series With Linear State Space Structure

---

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 intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.

---

Availability

No copy data

Detail Information

Series Title

-

Call Number

-

Publisher

Cham, Switzerland : ., 2016

Collation

XVII, 541

Language

English

ISBN/ISSN

978-3-319-28598-6

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

1

Subject(s)

-

Specific Detail Info

-

Statement of Responsibility

Víctor Gómez

Other Information

Cataloger

Rani

Source

-

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment