Procedures

SAS/ETS software includes the following SAS procedures:

ARIMA

ARIMA (Box-Jenkins) and ARIMAX (Box-Tiao) modeling and forecasting

AUTOREG

regression analysis with autocorrelated or heteroscedastic errors and ARCH and GARCH modeling

COMPUTAB

spreadsheet calculations and financial report generation

COUNTREG

regression modeling for dependent variables that represent counts

DATASOURCE

access to financial and economic databases

ENTROPY

maximum entropy-based regression

ESM

forecasting by using exponential smoothing models with optimized smoothing weights

EXPAND

time series interpolation, frequency conversion, and transformation of time series

FORECAST

automatic forecasting

LOAN

loan analysis and comparison

MDC

multinomial discrete choice analysis

MODEL

nonlinear simultaneous equations regression and nonlinear systems modeling and simulation

PANEL

panel data models

PDLREG

polynomial distributed lag regression

QLIM

qualitative and limited dependent variable analysis

SIMILARITY

similarity analysis of time series data for time series data mining

SIMLIN

linear systems simulation

SPECTRA

spectral and cross-spectral analysis

STATESPACE

state space modeling and automated forecasting of multivariate time series

SYSLIN

linear simultaneous equations models

TIMESERIES

analysis of time-stamped transactional data

TSCSREG

time series cross-sectional regression analysis

UCM

unobserved components analysis of time series

VARMAX

vector autoregressive and moving-average modeling and forecasting

X11

seasonal adjustment (Census X-11 and X-11 ARIMA)

X12

seasonal adjustment (Census X-12 ARIMA)

Macros

SAS/ETS software includes the following SAS macros:

%AR

generates statements to define autoregressive error models for the MODEL procedure

%BOXCOXAR

investigates Box-Cox transformations useful for modeling and forecasting a time series

%DFPVALUE

computes probabilities for Dickey-Fuller test statistics

%DFTEST

performs Dickey-Fuller tests for unit roots in a time series process

%LOGTEST

tests to determine whether a log transformation is appropriate for modeling and forecasting a time series

%MA

generates statements to define moving-average error models for the MODEL procedure

%PDL

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.

Access Interfaces to Economic and Financial Databases

In addition to PROC DATASOURCE, these SAS/ETS access interfaces provide seamless access to financial and economic databases:

SASECRSP

LIBNAME engine for accessing time series and event data residing in CRSPAccess database.

SASEFAME

LIBNAME engine for accessing time or case series data residing in a FAME database.

SASEHAVR

LIBNAME engine for accessing time series residing in a HAVER ANALYTICS Data Link Express (DLX) database.

The Time Series Forecasting System

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

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.