Adaptive number and position of temperature rungs

[pwinskill]

Currently challenging and time consuming to calibrate the number and positions of temperature rungs. This should be automated. See:
https://www.tandfonline.com/doi/abs/10.1080/10618600.2013.778779

Having too many rungs may result in disappearance of probability mass from some of the modes, see:
https://doi.org/10.1214/08-AAP555
https://doi.org/10.1214/EJP.v14-638

[pwinskill]

This will now come under the $tuning() phase.

This will allow the user to set a starting number of rungs and a maximum number of rungs.
The R side will then jump in and out of the MCMC, trying to estimate big Lambda and cobined that with a target average acceptance rate to calculate the required (min) number of rungs