Adaptively samples points for each parameter to obtain an estimate of the confidence intervals.

SupportRegionHiSSE(hisse.obj, n.points=1000,,, 
min.number.points=10, verbose=TRUE)



an object of class that contains the MLE from a model run.


indicates the number of points to sample.

the scaling multiplier that defines interval to randomly sample. By default the value is set to 0.1, meaning that values are drawn at random along an interval that encompasses 10 percent above and below the MLE.

defines the number lnL units away from the MLE to include. By default the value is set to 2.


sets the minimum number of points that can be returned. By default the value is set to 10.


a logical indicating whether progress should be printed to the screen. The default is TRUE.


This is the support region estimator for the new version of hisse.

Note the option. This roughly sets the variance for sampling points. If this seems to take a long while to find enough points within the desired likelihood region consider reducing to either 0.05 or, in some cases, 0.01.


SupportRegionHiSSE returns an object of class This is a list with elements:


the sampled confidence interval.


the sampled points that within 2lnL units from the MLE.


all points sampled by the adaptive sampler.


Beaulieu, J.M, and B.C. O'Meara. 2016. Detecting hidden diversification shifts in models of trait-dependent speciation and extinction. Syst. Biol. 65:583-601.

FitzJohn R.G., Maddison W.P., and Otto S.P. 2009. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Syst. Biol. 58:595-611.

Maddison W.P., Midford P.E., and Otto S.P. 2007. Estimating a binary characters effect on speciation and extinction. Syst. Biol. 56:701-710.

Nee S., May R.M., and Harvey P.H. 1994. The reconstructed evolutionary process. Philos. Trans. R. Soc. Lond. B Biol. Sci. 344:305-311.


Jeremy M. Beaulieu