Make default value of mh_jscale dependent on number of estimated parameters

We currently employ the default mh_jscale=0.2. This hardly ever fits as the optimal value is typically decreasing in the number of estimated parameters. I would propose to use the optimal value of Gelman et al. (1995) for the normal symmetric random walk Metropolis-Hastings of 2.38^2/npar as the default. That would break backward compatibility on files where the default was used, but would employ a more sensible starting value depending on the number of parameters estimated.