Introduction to Time Series Analysis

• What is a Time Series
• Autoregressive Models
• Stationary Process
• Assumptions
• Visual Tests
• AR(p) Model
• Backward Shift Operator
• AR(p) Parameter Estimation
• Assumptions and Tests for AR(p)
• Autocorrelation
• White Noise
• Moving Average (MA) Models
• Determining MA Parameters
• Autocorrelations for MA(1)
• Determining the Order MA(q)
• Determining the Order AR(p)
• Non-Stationarity: Integrated Models
• ARMA and ARIMA Models
• Non-Stationarity due to Seasonality
• Seasonal ARIMA (SARIMA) Models
• Case Study: Mobile Video
• Traffic Modeling – All Frames

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