Journal of Statistical Software

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Title State Space Modeling Using SAS
Author Selukar Rajesh
This article provides a brief introduction to the state space modeling capabilities in
SAS, a well-known statistical software system. SAS provides state space modeling in a
few di erent settings. SAS/ETS, the econometric and time series analysis module of the
SAS system, contains many procedures that use state space models to analyze univariate and multivariate time series data. In addition, SAS/IML, an interactive matrix language in the SAS system, provides Kalman ltering and smoothing routines for stationary and nonstationary state space models. SAS/IML also provides support for linear algebra and nonlinear function optimization, which makes it a convenient environment for general-purpose state space modeling.
Keywords Kalman lter, state space model, ARIMA, unobserved components, SAS/ETS, SAS/IML.
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