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State Space Modeling and Forecasting

The STATESPACE procedure provides automatic model selection, parameter estimation, and forecasting of state space models. (State space models encompass an alternative general formulation of multivariate ARIMA models.) The STATESPACE procedure includes the following features:

  • multivariate ARIMA modeling by using the general state space representation of the stochastic process

  • automatic model selection using Akaike’s information criterion (AIC)

  • user-specified state space models including restrictions

  • transfer function models with random inputs

  • any combination of simple and seasonal differencing; input series can be differenced to any order for any lag lengths

  • forecasts with confidence limits

  • ability to save selected and fitted model in a data set and reuse for forecasting

  • wide range of output options including the ability to print any statistics concerning the data and their covariance structure, the model selection process, and the final model fit

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