Time Series for Data Science: Analysis and Forecasting
Wayne A. Woodward (Southern Methodist University, Dallas, Texas, USA),Bivin Philip Sadler (Technical Assistant Professor, Southern Methodist University),Stephen Robertson
Time Series for Data Science: Analysis and Forecasting
Wayne A. Woodward (Southern Methodist University, Dallas, Texas, USA),Bivin Philip Sadler (Technical Assistant Professor, Southern Methodist University),Stephen Robertson
Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing, Holt Winters, ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs, and ensemble models composed of combinations of these models. Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy. Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics, Department of Transportation and the World Bank. There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use.
This item is not currently in-stock. It can be ordered online and is expected to ship in approx 2 weeks
Our stock data is updated periodically, and availability may change throughout the day for in-demand items. Please call the relevant shop for the most current stock information. Prices are subject to change without notice.
Sign in or become a Readings Member to add this title to a wishlist.