| Contents of SAS/ETS Software |
SAS/ETS software includes the following SAS procedures:
ARIMA (Box-Jenkins) and ARIMAX (Box-Tiao) modeling and forecasting
regression analysis with autocorrelated or heteroscedastic errors and ARCH and GARCH modeling
spreadsheet calculations and financial report generation
regression modeling for dependent variables that represent counts
fitting and simulating multivariate distributions using copula methods
access to financial and economic databases
maximum entropy-based regression
forecasting by using exponential smoothing models with optimized smoothing weights
time series interpolation, frequency conversion, and transformation of time series
automatic forecasting
loan analysis and comparison
multinomial discrete choice analysis
nonlinear simultaneous equations regression and nonlinear systems modeling and simulation
panel data models
polynomial distributed lag regression
qualitative and limited dependent variable analysis
modeling the statistical distribution of the severity of losses and other events
similarity analysis of time series data for time series data mining
linear systems simulation
spectral and cross-spectral analysis
state space modeling of time series
state space modeling and automated forecasting of multivariate time series
linear simultaneous equations models
identifying the time frequency for data sets containing time series data
analysis of time-stamped transactional data
time series cross-sectional regression analysis
unobserved components analysis of time series
vector autoregressive and moving-average modeling and forecasting
seasonal adjustment (Census X-11 and X-11 ARIMA)
seasonal adjustment (Census X-12 ARIMA)
SAS/ETS software includes the following SAS macros:
generates statements to define autoregressive error models for the MODEL procedure
investigates Box-Cox transformations useful for modeling and forecasting a time series
computes probabilities for Dickey-Fuller test statistics
performs Dickey-Fuller tests for unit roots in a time series process
tests to determine whether a log transformation is appropriate for modeling and forecasting a time series
generates statements to define moving-average error models for the MODEL procedure
generates statements to define polynomial distributed lag models for the MODEL procedure
These macros are part of the SAS AUTOCALL facility and are automatically available for use in your SAS program. Refer to SAS Macro Language: Reference for information about the SAS macro facility.
In addition to PROC DATASOURCE, these SAS/ETS access interfaces provide seamless access to financial and economic databases:
LIBNAME engine for accessing time series and event data residing in CRSPAccess database.
LIBNAME engine for accessing time or case series data residing in a FAME database.
LIBNAME engine for accessing time series residing in a HAVER ANALYTICS Data Link Express (DLX) database.
LIBNAME engine (experiemental) for accessing data items residing in the CRSP US Stock (STK) Database, the CRSP US Stock and Indices (IND) Database, the CRSP US Treasury (TRS) Database, or the CRSP/Compustat Merged (CCM) Database, which is created from data delivered via Standard and Poor’s Compustat Xpressfeed product.
SAS/ETS software includes an interactive forecasting system, described in Part IV. This graphical user interface to SAS/ETS forecasting features was developed with SAS/AF software and uses PROC ARIMA and other internal routines to perform time series forecasting. The Time Series Forecasting System makes it easy to forecast time series and provides many features for graphical data exploration and graphical comparisons of forecasting models and forecasts. (You must have SAS/GRAPH® installed to use the graphical features of the system.)
The Investment Analysis System, described in Part V, is an interactive environment for analyzing the time-value of money in a variety of investments. Various analyses are provided to help analyze the value of investment alternatives: time value, periodic equivalent, internal rate of return, benefit-cost ratio, and break-even analysis.