optim_doc: d2_min

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### 1.6 Unconstrained Newton-like optimization

This backend features a Newton-like algorithm. The user has to supply a Hessian function. No constraints are honoured. If the supplied Hessian function actually returns the inverse of the Hessian, set `inverse_hessian` to `true`. Supplying the inverse Hessian is preferable, if possible.

Returned value cvg will be `2` or `3` for success and `0` or `-1` for failure ( see nonlin_min for meaning). Returned structure outp will have the fields `niter`, `nobjf`, and `user_interaction`.

Interpretation of `Display`: if set to `"iter"`, some diagnostics are printed.