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Titlebook: Practical Time Series Analysis in Natural Sciences; Victor Privalsky Book 2023 The Editor(s) (if applicable) and The Author(s), under excl

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書目名稱Practical Time Series Analysis in Natural Sciences
編輯Victor Privalsky
視頻videohttp://file.papertrans.cn/754/753306/753306.mp4
概述Provides a unique tool to obtain exhaustive information about statistical properties.Includes mathematically proper forecasting.Contains many examples
叢書名稱Progress in Geophysics
圖書封面Titlebook: Practical Time Series Analysis in Natural Sciences;  Victor Privalsky Book 2023 The Editor(s) (if applicable) and The Author(s), under excl
描述.This book presents an easy-to-use tool for time series analysis and allows the user to concentrate upon studying time series properties rather than upon how to calculate the necessary estimates. The two attached programs provide, in one run of the program, a time and frequency domain description of scalar or multivariate time series approximated with a sequence of autoregressive models of increasing orders. The optimal orders are chosen by five order selection criteria. The results for scalar time series include time domain stochastic difference equations, spectral density estimates, predictability properties, and a forecast of scalar time series based upon the Kolmogorov-Wiener theory. For the bivariate and trivariate time series, the results contain a time domain description with multivariate stochastic difference equations, statistical predictability criterion, and information for calculating feedback and Granger causality properties in the bivariate case. The frequency domain information includes spectral densities, ordinary, multiple, and partial coherence functions, ordinary and multiple coherent spectra, gain, phase, and time lag factors. The programs seem to be unique and
出版日期Book 2023
關鍵詞Autoregressive; Stochastic Difference Equation; Time and Frequency Domain Analysis; Singular and Multiv
版次1
doihttps://doi.org/10.1007/978-3-031-16891-8
isbn_softcover978-3-031-16893-2
isbn_ebook978-3-031-16891-8Series ISSN 2523-8388 Series E-ISSN 2523-8396
issn_series 2523-8388
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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