Time series for data science : analysis and forecasting
- Boca Raton : CRC Press, 2022
- xxi, 506 p. ; ill., 26 cm
- Chapman & Hall/CRC texts in statistical science series .
Includes bibliographical references and index.
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.
9780367537944
Autoregression Statistics Big data Time-series analysis Information science