Standard syllabus
Advanced time series · Graduate · Statistics
Topics
Linear time series theory
- Stationarity, ergodicity, and autocovariance
- ARMA, ARIMA, and SARIMA models
- Identification, estimation, and diagnostics
- Forecasting theory: optimal linear predictors
- Seasonal and long-memory models (intro)
State space and spectral methods
- State space models and Kalman filter
- Structural time series models
- Spectral representation and periodograms
- Multivariate time series (VAR intro)
- Cointegration and error correction (overview)
Nonlinear and financial time series
- ARCH/GARCH models for volatility
- Threshold and regime-switching models (intro)
- Functional time series (overview)
- High-frequency data challenges (preview)
Pricing
Graduate-level rates are set on consultation. See the pricing page for K–12 and undergraduate rates.