Description Usage Arguments Details Value See Also Examples
Provide a check on Kuhn-Karush-Tucker conditions based on quantities already computed. Some of these used only for reporting.
1 2 |
par |
A vector of values for the parameters which are supposedly optimal. |
fn |
The objective function |
gr |
The gradient function |
hess |
The Hessian function |
upper |
Upper bounds on the parameters |
lower |
Lower bounds on the parameters |
maxfn |
Logical TRUE if function is being maximized. Default FALSE. |
control |
A list of controls for the function |
... |
The dot arguments needed for evaluating the function and gradient and hessian |
kktchk computes the gradient and Hessian measures for BOTH unconstrained and bounds (and masks) constrained parameters, but the kkt measures are evaluated only for the constrained case.
The output is a list consisting of
gmax |
The absolute value of the largest gradient component in magnitude. |
evratio |
The ratio of the smallest to largest Hessian eigenvalue. Note that this may be negative. |
kkt1 |
A logical value that is TRUE if we consider the first (i.e., gradient) KKT condition to be satisfied. WARNING: The decision is dependent on tolerances and scaling that may be inappropriate for some problems. |
kkt2 |
A logical value that is TRUE if we consider the second (i.e., positive definite Hessian) KKT condition to be satisfied. WARNING: The decision is dependent on tolerances and scaling that may be inappropriate for some problems. |
hev |
The calculated hessian eigenvalues, sorted largest to smallest?? |
ngatend |
The computed (unconstrained) gradient at the solution parameters. |
nnatend |
The computed (unconstrained) hessian at the solution parameters. |
1 | # genrose function code
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