Modeling Trend, Cycles, and Seasonality in Time Series Data Using PROC UCM

This lecture teaches students how to model, interpret, and predict time series data using UCMs. The UCM procedure analyzes and forecasts equally spaced univariate time series data using the Unobserved Components Models (UCM).

Learn how to

• analyze time series data using a novel class of models called the Unobserved Componenet Models (UCM)
• use the UCM procedure to find a suitable model for the series of interest, to obtain extensive model diagnostics, and to generate series forecasts and the forecasts of the constituent components
• get detailed understanding of the series dynamics by analyzing the plots of the estimated components.

Who should attend: Those who want to analyze time series data to uncover patterns such as trend, seasonal effects, and cycles using the latest techniques

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