SCA Forecasting and Modeling Package
The SCA Forecasting and Modeling Package provides comprehensive features for advanced forecasting applications. Among its many features are automatic Exponential Smoothing, Box-Jenkins ARIMA, regression, multiple-input transfer function, and multivariate time series modeling methods.
English
Supported Technologies
AIX,
DEC OpenVMS,
HP/UX,
Linux,
MVS(OS/390),
Netware,
OS/2 Warp,
Solaris/Sun OS,
Windows 95/98/ME,
Windows XP/2000/NT
Software
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Pricing
Users (# of seats), Server, System, Module
30000 to 250000
sales@scausa.com
312-455-0222
Additional Product Information
The SCA Statistical System is an software system that provides powerful and convenient forecasting capabilities that may be deployed as an integrated statistical modeling and forecasting engine or as a stand alone system. The SCA System contains proven modeling and forecasting capabilities are an essential part of the strategic planning and decision making of business and industry worldwide. The System's scope of capabilities also make it an excellent research and instructional tool. ;Scientific Computing Associates recognizes that the forecasting process is more than the calculation of forecast values. In a era of change and uncertainty, knowledge of system structure and the interplay of variables is important. Quantitative forecasting methods are invaluable in providing such knowledge.;Quantitative forecasting methods use analytical techniques and historical data as the basis for forecasting the future. To facilitate quantitative forecasting, the SCA System provides both model-based and ad hoc approaches.;For model-based approaches, univariate and multivariate time series models are employed. Ad hoc techniques include various exponential smoothing methods and moving average methods.;Univariate time series capabilities feature traditional Box-Jenkins ARIMA models as well as unidirectional models found in intervention and transfer function analysis. In addition, the SCA System features state-of-the-art multi-variable forecasting and time series methods using the most advanced techniques in the field including vector ARMA modeling and simulteneous transfer function modeling.