The primary objective in time series analysis is forecasting. Raw data often exhibits nonstationary behavior: trends, seasonal cycles, and heteroskedasticity. After data is transformed to a weakly stationary process, autoregressive moving average (ARMA) models may capture the remaining temporal dynamics to improve forecasting.
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- Partial requirement for: Ph.D., Arizona State University, 2018Note typethesis
- Includes bibliographical references (pages 119-131)Note typebibliography
- Field of study: Statistics