is_dnlp: Check if an Expression or Problem is DNLP-Compliant
In CVXR: Disciplined Convex Optimization
is_dnlp R Documentation
Check if an Expression or Problem is DNLP-Compliant
Description
Tests whether the object follows the Disciplined Nonlinear Programming
(DNLP) rules: smooth representable, i.e. linearizable-convex or
linearizable-concave.
Usage
is_dnlp(x, ...)
Arguments
x
An expression, objective, constraint, or Problem.
...
Not used.
Value
Logical scalar.
CVXR documentation built on Aug. 24, 2026, 9:10 a.m.
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| is_dnlp | R Documentation |
Check if an Expression or Problem is DNLP-Compliant
Description
Tests whether the object follows the Disciplined Nonlinear Programming (DNLP) rules: smooth representable, i.e. linearizable-convex or linearizable-concave.
Usage
is_dnlp(x, ...)
Arguments
x |
An expression, objective, constraint, or |
... |
Not used. |
Value
Logical scalar.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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