Introduction to time series and forecasting
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Summary
A general approach to Time Series Modelling and ModeLLing with ARMA Processes, which describes the development of a Stationary Process in Terms of Infinitely Many Past Values and the Autocorrelation Function.
- Type
- book
- Published
- 1998-09-01
- Cited by
- 5,174
- References
- 40
- Access
- Open access
- OpenAlex
- https://openalex.org/W2798056406
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:123940620
Keywords
Key (lock), Series (stratigraphy), Computer science, Calculus (dental), Order (exchange)
References
- Forecasting structural time series models and the kalman filter: Andrew Harvey, 1989, (Cambridge University Press), 554 pp., ISBN 0-521-32196-4
- Information And Exponential Families
- Inference for MA (1) processes with a root on or near the unit circle
- The Forecasting Accuracy of Major Time Series
- Regression and time series model selection in small samples
- The monte carlo newton-raphson algorithm
- Monte Carlo EM Estimation for Time Series Models Involving Counts
- Distribution of the Estimators for Autoregressive Time Series with a Unit Root
- Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
- Intervention Analysis with Applications to Economic and Environmental Problems
- Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models
- Application of Least Squares Regression to Relationships Containing Auto-Correlated Error Terms
- Matrices With Applications
- DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS
- The Estimation of the Order of an ARMA Process
- TIME‐REVERSIBILITY, IDENTIFIABILITY AND INDEPENDENCE OF INNOVATIONS FOR STATIONARY TIME SERIES
- Continuous Time Econometric Modelling.
- On continuous-time threshold ARMA processes
- ON THE CHOICE OF THE ORDER OF AUTOREGRESSIVE MODELS: A RANKING AND SELECTION APPROACH
- Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
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