| 书目名称 | Linear Time Series with MATLAB and OCTAVE | | 编辑 | Víctor Gómez | | 视频video | | | 概述 | Provides a theoretical and practical introduction to linear univariate and multivariate time series.Includes numerous examples and real-world applications that help the reader to quickly grasp the con | | 丛书名称 | Statistics and Computing | | 图书封面 |  | | 描述 | .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 als | | 出版日期 | Textbook 2019 | | 关键词 | Linear time series; MATLAB; State space models; Kalman filter; Univariate time series; Multivariate time | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-20790-8 | | isbn_softcover | 978-3-030-20792-2 | | isbn_ebook | 978-3-030-20790-8Series ISSN 1431-8784 Series E-ISSN 2197-1706 | | issn_series | 1431-8784 | | copyright | Springer Nature Switzerland AG 2019 |
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发表于 2025-3-21 20:08:26
