The following table outlines the options in PROC NLP classified by function. An alphabetical list of options is provided in the Dictionary of Options.
Table 8.1: Functional Summary
Description |
Statement |
Option |
---|---|---|
Input Data Set Options: |
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Input data set |
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Initial values and constraints |
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Quadratic objective function |
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Program statements |
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Skip missing value observations |
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Output Data Set Options: |
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Variables and derivatives |
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Result parameter values |
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Program statements |
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Combine various OUT…statements |
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CRP Jacobian in the OUTEST= data set |
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Derivatives in the OUT= data set |
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Grid in the OUTEST= data set |
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Hessian in the OUTEST= data set |
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Iterative output in the OUTEST= data set |
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Jacobian in the OUTEST= data set |
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NLC Jacobian in the OUTEST= data set |
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Time in the OUTEST= data set |
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Optimization Options: |
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Minimization method |
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Update technique |
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Version of optimization technique |
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Line-search method |
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Line-search precision |
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Type of Hessian scaling |
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Start for approximated Hessian |
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Iteration number for update restart |
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Initial Value Options: |
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Produce best grid points |
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Infeasible points in grid search |
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Pseudorandom initial values |
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Constant initial values |
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Derivative Options: |
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Finite-difference derivatives |
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Finite-difference derivatives |
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Compute finite-difference interval |
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Use only diagonal of Hessian |
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Test gradient specification |
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Constraint Options: |
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Range for active constraints |
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LM tolerance for deactivating |
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Tolerance for dependent constraints |
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Sum all observations for continuous functions |
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Evaluate each observation for continuous functions |
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Termination Criteria Options: |
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Maximum number of function calls |
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Maximum number of iterations |
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Minimum number of iterations |
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Upper limit on real time |
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Absolute function convergence criterion |
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Absolute function convergence criterion |
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Absolute gradient convergence criterion |
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Absolute parameter convergence criterion |
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Relative function convergence criterion |
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Relative function convergence criterion |
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Relative gradient convergence criterion |
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Relative gradient convergence criterion |
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Relative parameter convergence criterion |
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Used in FCONV, GCONV criterion |
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Used in XCONV criterion |
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Covariance Matrix Options: |
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Type of covariance matrix |
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factor of COV matrix |
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Determine factor of COV matrix |
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Absolute singularity for inertia |
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Relative M singularity for inertia |
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Relative V singularity for inertia |
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Threshold for Moore-Penrose inverse |
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Tolerance for singular COV matrix |
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Profile confidence limits |
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Printed Output Options: |
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Display (almost) all printed output |
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Suppress all printed output |
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Reduce some default output |
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Reduce most default output |
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Display initial values and gradients |
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Display optimization history |
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Display Jacobian matrix |
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Display crossproduct Jacobian matrix |
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Display Hessian matrix |
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Display Jacobian of nonlinear constraints |
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Display values of grid points |
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Display values of functions in LSQ, MIN, MAX |
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Display approximate standard errors |
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Display covariance matrix |
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Display eigenvalues for covariance matrix |
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Print code evaluation problems |
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Print measures of real time |
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Display model program, variables |
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Display compiled model program |
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Step Length Options: |
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Damped steps in line search |
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Maximum trust region radius |
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Initial trust region radius |
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Profile Point and Confidence Interval Options: |
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Factor relating discrepancy function to quantile |
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Scale for values written to OUTEST= data set |
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Upper bound for confidence limit search |
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Write all confidence limit parameter estimates to OUTEST= data set |
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Miscellaneous Options: |
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Number of accurate digits in objective function |
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Number of accurate digits in nonlinear constraints |
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General singularity criterion |
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Do not compute inertia of matrices |
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Check optimality in neighborhood |