as.statusCode | R Documentation |

Below we provide a brief, technical description of each status code followed by a more colloquial, less precise desciption.

0,‘OK’: Optimization succeeded. Everything seems fine.

1,‘OK/green’: Optimization succeeded, but the sequence of iterates has not yet converged (Mx status GREEN). This condition is only detected by NPSOL. The solution is likely okay. You might want to re-run the model from its final esimates to resolve this.

2,‘infeasible linear constraint’: The linear constraints and bounds could not be satisfied. The problem has no feasible solution. Right now, it should not be possible obtain this status code, so call Ripley's.

3,‘infeasible non-linear constraint’: The nonlinear constraints and bounds could not be satisfied. The problem may have no feasible solution. Sometimes this happens when your starting values do not satisfy the constraints. Also, optimization could not satisfy the constraints and get a better fit.

4,‘iteration limit’: Optimization was stopped prematurely because the iteration limit was reached (Mx status BLUE). You might want to rerun:

`m1 = mxRun(m1)`

or increase the iteration limit (see`mxOption`

). The optimizer took all the steps it could and did not finish. You can increase the number of steps or get better starting values.5,‘not convex’: The Hessian at the solution does not appear to be convex (Mx status RED). There may be more than one solution to the model. See

`mxCheckIdentification`

. I would not trust this solution; it does not appear to be a good one. Perhaps, try`mxTryHard`

.6,‘nonzero gradient’: The model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED). I would not trust this solution; it does not appear to be a good one. To search nearby, see

`mxTryHard`

.7,‘bad deriv’: You have provided analytic derivatives. However, your provided derivatives differ too much from numerically approximated derivatives. Double check your math.

9,‘internal error’: An input parameter was invalid. The most likely cause is a bug in the code. Please report occurrences to the OpenMx developers.

10,‘infeasible start’: Starting values were infeasible. Modify the start values for one or more parameters. For instance, set means to their measured value, or set variances and covariances to plausible values. See

`mxAutoStart`

and`mxTryHard`

.

```
as.statusCode(code)
```

`code` |
a character or numeric vector of optimizer status code |

`mxBootstrap`

`summary.MxModel`

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