A Course in Time Series Analysis by Daniel Peña, George C. Tiao, Ruey S. Tsay
Publisher: Wiley-Interscience | 2000 | ISBN: 047136164X | 483 pages | PDF (scan) | 19,7 MB
Publisher: Wiley-Interscience | 2000 | ISBN: 047136164X | 483 pages | PDF (scan) | 19,7 MB
A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems.