Linear Time Series with MATLAB and OCTAVE
This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces read
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Víctor Gómez
Linear Time Series with MATLAB and OCTAVE
QUANTLETS
Statistics and Computing Series Editor Wolfgang Karl Härdle, Humboldt-Universität zu Berlin, Berlin, Germany
Statistics and Computing (SC) includes monographs and advanced texts on statistical computing and statistical packages.
More information about this series at http://www.springer.com/series/3022
Víctor Gómez
Linear Time Series with MATLAB and OCTAVE
123
Víctor Gómez General Directorate of Budgets Ministry of Finance and Public Administrations Madrid, Spain
Quantlets may be downloaded from http://extras.springer.com or via a link on http://www. springer.com/978-3-030-20789-2 or www.quantlet.org for a repository of quantlets. ISSN 1431-8784 ISSN 2197-1706 (electronic) Statistics and Computing ISBN 978-3-030-20789-2 ISBN 978-3-030-20790-8 (eBook) https://doi.org/10.1007/978-3-030-20790-8 Mathematics Subject Classification (2010): 62-01, 62-02, 62-04, 62-07, 62M15, 62M10, 62M20, 62J05 © Springer Nature Switzerland AG 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To my wife María C. and my daughter Berta
Preface
The motivation of this book is to provide time series students and researchers with a software package called SSMMATLAB, written in MATLAB, that will allow them to work with general state space models. Since many time series models used in practice can be put into state space form, special functions have been written for the most usual ones, such as multiplicative ARIMA and VARMA models, cointegrated VARMA models, VARMAX models in echelon form, transfer function models, univariate structural models, like those considered by Harvey (1993, Chap. 4) or Kitagawa and Gersch (1996), and ARIMA model-b
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