Time Series Analysis and Business Forecasting (Special paper)
STAT3015Y(5)*
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Description
Examples of time series. Time series plot. Model-building strategy. Classical trend and seasonal model.
Additive and multiplicative models. Decomposition. Exponential smoothing. Estimation. Forecasting using
Holt-Winters method. Time series and stochastic processes. Autocovariance function. Random walk.
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Moving Average. White Noise. Stationarity. Models for stationary time series : general linear process, MA
processes. AR processes. Invertibility. Box-Jenkins methods. ARIMA and SARIMA processes. Models for
non-stationary time series. Differencing. Model specification. Properties of sample acf and pacf.
Nonstationarity. AIC criterion. Model Estimation and diagnostics. Residual analysis. Box-Pierce and Ljung-
Box statistics. Forecasting. Using R Statistical Language for time series analysis.
