Data Driven Model Learning for Engineers: With Applications to Univariate Time Series
Data Driven Model Learning for Engineers: With Applications to Univariate Time Series
English | 2023 | ISBN: 3031316355 | 218 Pages | PDF | 7.4 MB
English | 2023 | ISBN: 3031316355 | 218 Pages | PDF | 7.4 MB
The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail.