surfaceSummary {surface}

Summarize SURFACE Output

Description

Extracts the most important results from the output of the forward, backward, or both phases of a SURFACE analysis

Usage

surfaceSummary(fwd = NULL, bwd = NULL)

Arguments

fwd

A list returned by surfaceForward (which may be stored as the $fwd component of the list returned by runSurface)

bwd

A list returned by surfaceBackward (which may be stored as the $bwd component of the list returned by runSurface)

Details

If both fwd and bwd are provided, both phases of the analysis will be summarized together

Value

A list with the following components:

n_steps

number of iterations in the stepwise analysis

lnls

matrix of traits-by-iterations, giving the log-likelihood for each trait at each iteration of the analysis

n_regimes_seq

matrix of the summaries of regime structure at each iteration of the model

aics

vector giving the AICc value at each step

shifts

shifts present in the final fitted Hansen model

n_regimes

summary of regime structure of the final fitted Hansen model (see note below)

alpha

estimate of alpha for each trait in the final model

sigma_squared

estimate of sigma_squared for each trait in the final model

theta

matrix of estimated optima (one per regime per trait) in the final model

Note

The elements n_regimes_seq and n_regimes contain measures of the regime structure in a SURFACE analysis (for each iteration, and in the final model, respectively). The measures returned are: k (the number of regime shifts, counting the basal regime as 1), kprime, (the number of regimes, some of which may be reached by multiple shifts), deltak (k-kprime, a measure of convergence), c (the number of shifts to convergent regimes, another measure of convergence), kprime_conv (the number of convergent regimes shifted to multiple times), and kprime_nonconv (the number of nonconvergent regimes only shifted to once)

Author(s)

Travis Ingram

References

Ingram, T. & Mahler, D.L. (2013) SURFACE: detecting convergent evolution from comparative data by fitting Ornstein-Uhlenbeck models with stepwise AIC. Methods in Ecology and Evolution 4: 416-425.

See Also

surfaceForward, surfaceBackward

Examples

	## Not run: 
data(surfaceDemo)
tree<-surfaceDemo$tree
dat<-surfaceDemo$sim$dat
result<-runSurface(tree,dat)
surfaceSummary(result$fwd,result$bwd)
	
## End(Not run)