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| The MODEL Procedure |
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- Overview: MODEL Procedure
- Getting Started: MODEL Procedure
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Syntax: MODEL Procedure
- Functional Summary
- PROC MODEL Statement
- BOUNDS Statement
- BY Statement
- CONTROL Statement
- ENDOGENOUS Statement
- ERRORMODEL Statement
- ESTIMATE Statement
- EXOGENOUS Statement
- FIT Statement
- ID Statement
- INCLUDE Statement
- INSTRUMENTS Statement
- LABEL Statement
- MOMENT Statement
- OUTVARS Statement
- PARAMETERS Statement
- Programming Statements
- RANGE Statement
- RESET Statement
- RESTRICT Statement
- SOLVE Statement
- TEST Statement
- VAR Statement
- WEIGHT Statement
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Details: Estimation by the MODEL Procedure
- Estimation Methods
- Properties of the Estimates
- Minimization Methods
- Convergence Criteria
- Troubleshooting Convergence Problems
- Iteration History
- Computer Resource Requirements
- Testing for Normality
- Heteroscedasticity
- Testing for Autocorrelation
- Transformation of Error Terms
- Error Covariance Structure Specification
- Ordinary Differential Equations
- Restrictions and Bounds on Parameters
- Tests on Parameters
- Hausman Specification Test
- Chow Tests
- Profile Likelihood Confidence Intervals
- Choice of Instruments
- Autoregressive Moving-Average Error Processes
- Distributed Lag Models and the %PDL Macro
- Input Data Sets
- Output Data Sets
- ODS Table Names
- ODS Graphics
- Details: Simulation by the MODEL Procedure
- Programming Language Overview: MODEL Procedure
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Examples: MODEL Procedure
- OLS Single Nonlinear Equation
- A Consumer Demand Model
- Vector AR(1) Estimation
- MA(1) Estimation
- Polynomial Distributed Lags by Using %PDL
- General Form Equations
- Spring and Damper Continuous System
- Nonlinear FIML Estimation
- Circuit Estimation
- Systems of Differential Equations
- Monte Carlo Simulation
- Cauchy Distribution Estimation
- Switching Regression Example
- Simulating from a Mixture of Distributions
- Simulated Method of Moments—Simple Linear Regression
- Simulated Method of Moments—AR(1) Process
- Simulated Method of Moments—Stochastic Volatility Model
- Duration Data Model with Unobserved Heterogeneity
- EMM Estimation of a Stochastic Volatility Model
- Illustration of ODS Graphics
- References
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