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题名/责任者:

Time series analysis for data science : analysis and forecasting / Wayne A. Woodward, Bivin Philip Sadler and Stephen Robertson.

版本说明:

First edition.

出版发行项:

Boca Raton : CRC Press, 2022.

ISBN:

9780367537944

ISBN:

036753794X

ISBN:

9780367543891

ISBN:

0367543893

载体形态项:

xxi, 506 pages : illustrations (black and white) ; 26 cm.

丛编说明:

Statistics

个人责任者:

Woodward, Wayne A., author.

附加个人名称:

Sadler, Bivin Philip, author.

附加个人名称:

Robertson, Stephen (Lecturer in statistics), author.

论题主题:

Time-series analysis.

论题主题:

Autoregression (Statistics)

论题主题:

Big data.

中图法分类号:

O211.61

书目附注:

Includes bibliographical references and index.

内容附注:

Working with data collected over time -- Exploring time series data -- Statistical basics for time series analysis -- The frequency domains -- ARMA models -- ARMA fitting and forecasting -- ARIMA, seasonal, and ARCH/GARCH models -- Time series regression -- Model assessment -- Multivariate time series -- Deep neural network based time series models.

摘要附注:

"This book will be written at a level that requires little or no calculus but does not shy away from giving students more than a cursory understanding of the fundamentals and techniques involved. It will cover time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It gives more emphasis to classical ARMA and ARIMA models than is found in similar-level texts. Knowing that students and practitioners want to find a forecast that "works" and don't want to be constrained to a single forecasting strategy, we discuss techniques of ensemble modeling for combining information from several strategies (multivariate, VAR, neural networks, etc.)"--

豆瓣简介：