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SAS 9.2 Documentation
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SAS/ETS(R) 9.2 User's Guide
PDF
Contents
About
Credits and Acknowledgments
What's New in SAS/ETS
General Information
Introduction
Working with Time Series Data
Date Intervals, Formats, and Functions
SAS Macros and Functions
Nonlinear Optimization Methods
Procedure Reference
The ARIMA Procedure
The AUTOREG Procedure
The COMPUTAB Procedure
The COUNTREG Procedure
The DATASOURCE Procedure
The ENTROPY Procedure
The ESM Procedure
The EXPAND Procedure
The FORECAST Procedure
The LOAN Procedure
The MDC Procedure
The MODEL Procedure
The PANEL Procedure
The PDLREG Procedure
The QLIM Procedure
The SIMILARITY Procedure
The SIMLIN Procedure
The SPECTRA Procedure
The STATESPACE Procedure
The SYSLIN Procedure
The TIMESERIES Procedure
The TSCSREG Procedure
The UCM Procedure
The VARMAX Procedure
The X11 Procedure
The X12 Procedure
Data Access Engines
The SASECRSP Interface Engine
The SASEFAME Interface Engine
The SASEHAVR Interface Engine
Time Series Forecasting System
Overview of the Time Series Forecasting System
Getting Started with Time Series Forecasting
Creating Time ID Variables
Specifying Forecasting Models
Choosing the Best Forecasting Model
Using Predictor Variables
Command Reference
Window Reference
Forecasting Process Details
Investment Analysis
Overview
Portfolios
Investments
Computations
Analyses
Details
Index here
Product
Release
SAS/ETS
9.2
Type
Usage and Reference
Copyright Date
March 2008
Last Updated
15Apr2008
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The MDC Procedure
The MDC Procedure
Overview: MDC Procedure
Getting Started: MDC Procedure
Conditional Logit: Estimation and Prediction
Nested Logit Modeling
Multivariate Normal Utility Function
HEV and Multinomial Probit: Heteroscedastic Utility Function
Parameter Heterogeneity: Mixed Logit
Syntax: MDC Procedure
Functional Summary
PROC MDC Statement
MDCDATA Statement
BOUNDS Statement
BY Statement
ID Statement
MODEL Statement
NEST Statement
NLOPTIONS Statement
OUTPUT Statement
RESTRICT Statement
UTILITY Statement
Details: MDC Procedure
Multinomial Discrete Choice Modeling
Multinomial Logit and Conditional Logit
Heteroscedastic Extreme-Value Model
Mixed Logit Model
Multinomial Probit
Nested Logit
Decision Tree and Nested Logit
Model Fit and Goodness-of-Fit Statistics
OUTEST= Data Set
ODS Table Names
Examples: MDC Procedure
Binary Data Modeling
Conditional Logit and Data Conversion
Correlated Choice Modeling
Testing for Homoscedasticity of the Utility Function
Choice of Time for Work Trips: Nested Logit Analysis
Hausman’s Specification and Likelihood Ratio Tests
Acknowledgments
References
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Copyright © 2007 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
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