040 __ |a LBSOR/DLC |b eng |e rda |c DLC |d OCLCF |d OCLCO |d UKMGB |d OCLCO

245 10 |a Time series analysis for data science : |b analysis and forecasting / |c Wayne A. Woodward, Bivin Philip Sadler and Stephen Robertson.

505 0_ |a 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.

520 __ |a "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.)"-- |c Provided by publisher.