various updates

CIs for HMM and HSMMs appear to work well unless you have a low
parameter to value ratio.  CIs probably not great for tpm parameters on
the boundary, but that is typical.  Rewrote portions of the likelihood
computation and it is substantially faster.  Updated some of the plot
code.
Vectorized likelihood calculation and bootstrap CIs

The likelihood calculation was largely vectorized and I added bootstrap
CIs with multicore support on a local machine.  These are reasonably
fast to compute for HMMs, but pretty slow for HSMMs.  Profile likelihood
intervals may be a good compromise between using the finite differences
Hessian and bootstrapping.
readme update
Rcpp support

Rcpp support for both HMMs and HSMMs., both in fitting models and
obtaining CIs.  60% increase in speed for the last HSMM example.  Gains
probably bigger for long time series and many behavioral states.  I
could move more code to C++, but that part of the code is trickier and
I'm not sure if the gain is worth the effort.
trap problems with CI calculation

return Hessian as part of results
Merge branch 'master' of github.com:bbolker/move.HMM

Conflicts:
	DESCRIPTION
	R/move.HMM.mle.R
	R/move.HSMM.mle.R