The SCA Statistical System is available for personal computers, unix workstations, and mainframe computing environments. The information provided below focuses on the unix workstation and mainframe version of SCA software. The SCA System gives you the power to analyze time series data using comprehensive modeling capabilities and delivers accurate forecasts that you can depend on. The SCA System is the solution to your modeling and forecasting needs. The System's flexibility, ease of use, and ability to grow with its user form an impressive combination. You may choose among the modules listed below to address your individual forecasting and modeling needs:
|SCA Products||General Description|
|SCA-UTS||Univariate time series modeling and analysis including Box-Jenkins ARIMA, transfer function, and intervention models.|
|Extended UTS||Extended capabilities for automatic outlier detection and adjustment.|
|SCA-EXPERT||Automatic time series modeling using an advanced expert system approach.|
|SCA-ECON/M||Econometric modeling using simultaneous transfer function (STF) modeling. Also includes seasonal adjustment capabilities.|
|SCA-MTS||Multivariate time series modeling and analysis using vector ARMA models.|
|SCA-GSA||The GSA component provides commonly used general statistical analysis capabilities including descriptive statistics, multiple-linear regression, ANOVA, nonparametric statistics and more. The GSA module is an integrated component of all SCA Editions|
Univariate Time Series Modeling and Analysis
The SCA-UTS product includes extensive forecasting and time series modeling capabilities. It is this fundamental module on which other SCA forecasting and time series products are built. The SCA-UTS product focuses on user directed modeling capabilities, providing all the necessary tools to identify, estimate, diagnostically check, and forecast various time series models. The SCA-UTS product features,Box-Jenkins ARIMA models Lagged (dynamic) regression Regression with autocorrelated errors Convenient transfer function modeling Intervention (impact) analysis Spectral analysis Exponential smoothing using Simple, Double, Holt's, Winters' additive, Winters' Multiplicative, Seasonal indicator, and Harmonic smoothing methods Trading day adjustment Time series simulation Constrained parameter estimation Exact estimation algorithm
Extended capabilities for automatic outlier detection and adjustment
The SCA Extended UTS product provides cutting edge capabilities to conveniently handle contaminated or interrupted time series that may otherwise distort the underlying model structure, cause bias in parameter estimates, and lead to a deterioration in forecast performance. The Extended UTS product provides,Automatic outlier detection and adjustment capabilities that allow for the joint estimation of outlier effects and model parameters using an algorithm published by C. Chen and L.-M. Liu Automatically handles level shifts, temporary changes, additive, and innovational outliers Model identification and estimation with missing data Weighted model estimation effective in handling clustered outliers, and desensitizing parameter estimates from temporary structural changes in a time series Better forecasting results by special handling of outliers occurring at the end of a time series Improved estimation of intervention and transfer function models (removes bias in parameter estimates and avoids inflated variance) Includes the complete capabilities of SCA-UTS
Automatic time series modeling using an expert system algorithm
The SCA-EXPERT product employs an intelligent algorithm for automatic time series modeling. It is very easy to use, and is an asset to novices and experts alike, offering a quick and effective solution to handle repetitive modeling tasks. The SCA-EXPERT product features,Automatic identification of seasonal and non-seasonal ARIMA models Automatic transfer function modeling and intervention (impact) analysis Automatic vector ARMA modeling Reliable and accurate results relieving mundane modeling chores Manual override of models allowing complete flexibility Includes the complete capabilities of SCA-UTS
Traditional econometric modeling and time series analysis are blended in the capabilities present the SCA-ECON/M Module. Using this approach, many potential problems found in classical econometric analysis are avoided. One major problem of traditional econometric models is the assumption that disturbance (error) components are serially independent. Such an assumption can cause erroneous results when econometric models are applied to time series data. Now ARIMA models can be employed in the disturbance term of each equation in the system of equations. An added feature is that the coefficient of each input variable of an equation can be represented in either a linear or a rational form. This class of econometric models is also referred to a simultaneous transfer function(STF) models, or as rational distributed lag structured form (RSF) models.
Comprehsensive model identification techniques Conditional and exact maximum likelihood estimation Principal component analyses Canonical analysis
The multivariate extensions to the univariate sample autocorrelation function (PACF) are provided. They are sample cross-correlation matrices (CCM) and stepwise autoregressive fits(STEPAR). Additionally, the multivariate extensions of the univariate extended sample autocorrelation function (EACF) and the smallest canonical correlation (SCAN) are also provided. These extensions, developed by G.C. Tiao and R.S. Tsay, are very effective in the identification of mixed ARMA models and in discovering underlying relationships between series.
Parameters of a vector model can be estimated using either a conditional or exact maximum likelihood algorithm. In addition, ARMA parameters may be held to fixed values during the estimation process (such as zero), or can be constrained to be equal to other parameters.
Descriptive statistics and correlation Plots, histograms, and two-way tables Multiple regression analysis One-way to n-way ANOVA Analysis of covariance Two-sample tests of significance Cross tabulation Nonparametric statistics Distribution and model simulation
Same command language at all computing levels On-line HELP and prompting Extendability to handle user prepared procedures or programs Access to the computer's operating system while in an SCA session Dynamic storage allocation Commands to save and retrieve the System's memory between user sessions Data generation and editing, sorting and ranking Interface with other software
VAX, AlphaVax, AlphaDec, VaxStation and DECstation (VMS, OpenVMS, OSF1, ULTRIX) SUN, HP, RS/6000, Silicon Graphics, and other UNIX workstations