trained space (if such mode exists). Thus this option is useful for any optimization where we want to find the mode in the original constrained parameter space.</p>
<p>If the Jacobian adjustment is included, the optimization returns parameter values that correspond to a mode in the unconstrained space. This is useful, for example, if we want to make a distributional approximation of the posterior at the mode (see, <a href="../cmdstan-guide/laplace_sample_config.html">Laplace sampling</a>, as then Jacobian a