modelAveRates: Model average rates at tips and nodes

Description Usage Arguments Details Author(s) References

Description

Summarizes reconstructions from a single model or a set of models and returns model averaged rates.

Usage

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GetModelAveRates(x, AIC.weights=NULL, type=c("tips", "nodes", "both"),
bound.par.matrix=cbind(c(0,-1000,0,0,0),c(1000,1000,1000,3,1000)) )

Arguments

x

a hisse.states object, a hisse.states.geosse object, a muhisse.states or a list of such objects. A list of model can only include models of one type.

AIC.weights

a numeric vector with length equal to the number of models in the list 'x'. This is the AICw for each of the models to be averaged. If 'AIC.weights==NULL' (the default value) then function will compute the AICw for the models in the set from the $AIC value for each model.

type

one of "tips", "nodes", or "both" (the default). This controls whether only the averaged rates for the tips, nodes or both should be returned. If tips or nodes is chosen the output will be a matrix and if both are returned the output will be a list.

bound.par.matrix

A numeric matrix with exactly 5 rows and 2 columns to set the limits for the model parameters. First column is the minimum value and second column is the maximum value (both inclusive). The rows are the model parameter in this fixed order: turnover, net diversification, speciation, extinction fraction, and extinction.

Details

Provides a data frame model-averaged rates for all possible configurations of the model parameters (i.e., turnover, net.div, speciation, extinction, or extinction.fraction), either for all tips or for all nodes. As with the plotting function, if you give a single hisse.state object, it uses that, and the rates account for uncertainty in the marginal probabilities of the states; if you give it a list of them, it will model-average the results (it assumes the trees are the same) in addition to accounting for uncertainty in the marginal probabilities at tips and nodes. If 'AIC.weights==NULL', then the models in the set do not require the '$AIC' element to compute the AICw. Otherwise the function will return an error message.

Author(s)

Jeremy M. Beaulieu

References

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.


hisse documentation built on Nov. 16, 2021, 9:09 a.m.