lity and gradient calculation</h3>
<p>During each leapfrog step, the log probability function and its
gradient must be calculated. This is where most of the time in the
Stan algorithm is spent. This log probability function, which is
used by the sampling algorithm, is defined over the unconstrained
parameters.</p>
<p>The first step of the calculation requires the inverse transform of
the unconstrained parameter values back to the constrained parameters
in terms of which the model is defined. There is no err