Linear Time Series With Matlab And Octave
Download Linear Time Series With Matlab And Octave PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Linear Time Series With Matlab And Octave book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
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 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 using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ‘Multivariate Time Series With Linear State Space Structure’, by the same author, if they require more details.
Time Series and Networks Analysis
Author: Theodoros Karakasidis
language: en
Publisher: Springer Nature
Release Date: 2025-08-15
This textbook provides students with a hands-on introduction to time series analysis. Readers will learn the potential of the methods but also benefit from a step-by-step guide to apply them on simple data, as well as applications in real science in domains such as physics, environmental science, physics of fluids, simulation analysis etc. The authors emphasize application of the techniques and modern methodologies for time series analysis, using examples to demonstrate techniques introduced, including detailed, step-by-step solutions. Octave and Matlab are used as the computational environment for the applications, since the readers can find programs easily for many applications. The commands are clearly explained and the files are provided in the text and online.
Mathematics of the Discrete Fourier Transform (DFT)
"The DFT can be understood as a numerical approximation to the Fourier transform. However, the DFT has its own exact Fourier theory, and that is the focus of this book. The DFT is normally encountered as the Fast Fourier Transform (FFT)--a high-speed algorithm for computing the DFT. The FFT is used extensively in a wide range of digital signal processing applications, including spectrum analysis, high-speed convolution (linear filtering), filter banks, signal detection and estimation, system identification, audio compression (such as MPEG-II AAC), spectral modeling sound synthesis, and many others. In this book, certain topics in digital audio signal processing are introduced as example applications of the DFT"--Back cover