Linear Time Series with MATLAB and OCTAVE. 1st ed. 2019

種類:

電子ブック

責任表示:

by Víctor Gómez

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2019

著者名:

• Gómez, Víctor.
• SpringerLink (Online service)

シリーズ名:

Statistics and Computing ;

ISBN:

9783030207908 [3030207900]    

注記:

Preface -- Software Installation -- Stationarity, VARMA and ARIMA Models -- VARMAX and Transfer Function Models -- Unobserved Components in Univariate Series -- Spectral Analysis -- Computing Echelon Forms by Polynomial Methods -- Multivariate Structural Models -- Cointegrated VARMA Models -- Simulation of Common Univariate and Multivariate Models -- The State Space Model -- SSMMATLAB Examples by Subject -- Author Index -- Subject Index.
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 readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction u

ローカル注記:

学内専用E-BOOKS (local access only)