Abstract
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 different 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 filtering 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.
Highlights
SAS software (SAS Institute Inc. 2008a) offers a set of solutions for enterprise-wide business users and provides a powerful fourth-generation programming language for performing tasks such as data management, report writing and graphics, statistical and mathematical analysis, and operations research
This article provides a brief introduction to the state space modeling capabilities that are available in SAS/ETS (SAS Institute Inc. 2010), the econometric and time series analysis module of the SAS system, and in SAS/IML (SAS Institute Inc. 2008b), the SAS interactive matrix language
The local level model is an example of a unobserved components model (UCM) that decomposes the response series into two unobserved components: the level component μt and the irregular component t. It is a natural starting point in this analysis because the yearly water level of a large river, in the absence of major external shocks, can be expected to remain relatively constant for a long time. You can fit this model to the Nile data by using the UCM procedure as follows: proc ucm data = nile; id year interval = year; model waterlevel; irregular plot = smooth; level checkbreak plot = smooth; estimate plot = residual; forecast plot = forecasts lead = 10 alpha = 0.5; run; The PROC UCM statement signifies the start of the UCM procedure and specifies the input data set, nile, which contains the response series
Summary
SAS software (SAS Institute Inc. 2008a) offers a set of solutions for enterprise-wide business users and provides a powerful fourth-generation programming language for performing tasks such as data management, report writing and graphics, statistical and mathematical analysis, and operations research. This article provides a brief introduction to the state space modeling capabilities that are available in SAS/ETS (SAS Institute Inc. 2010), the econometric and time series analysis module of the SAS system, and in SAS/IML (SAS Institute Inc. 2008b), the SAS interactive matrix language.
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