geiger (version 2.0.6.2)

startingpt.mecca: starting values for MECCA

Description

This function takes the output of calibrateMecca along with observed data and partial least squares loadings and outputs starting values and tuning parameters for the ABC-MCMC (Wegmann et al. 2009).

Usage

startingpt.mecca(calibrationOutput, phy, cladeMean, cladeVariance,
                 tolerance = 0.01, plsComponents, BoxCox = TRUE)

Arguments

calibrationOutput

The output from calibrateMecca

phy

A time calibrated phylogeny in "phylo" format

cladeMean

A named vector of trait means. All tips in the tree must be represented

cladeVariance

A names vector of trait variances. All tips in the tree must be represented. If only one taxon is present, use 0 for the variance

tolerance

The proportion of calibrations simulations that fall closest to the oberved data that will be retained to compute MECCA tuning parameters

plsComponents

a matrix of Partial Least Squares component loadings

BoxCox

Logical - Should Summary Statistics be Box-Cox transformed? Default is yes and is recommended

Value

$tuning

a matrix containing starting values and proposal widths for trait evolution parameters

$startingBirth

Starting value for speciation

$startingDeath

Starting value for extinction

$dcrit

the criticial distance - simulated data must fall within this distance of the observed data in order to be accepted

$obsTraits

the observed data

$plsObserved

Partial Least Squared transformed observed data

$plsLoadings

Partial Least Squared componenent loadings - these are used to transform data during the MCMC

Details

You will need to compute PLS loadings using the package "pls" prior to running this function. MECCA performs extremely poorly if summaries are not PLS transformed. If Bayes Factors are to be computed to perform model selection (Leuenberger and Wegmann 2010), raw summaries will need to be used in the post-sampling adjustment step. However, PLS transformed summaries can still be used in the acceptance/rejection step of the MCMC and can also be used to determine which simulations to retain

References

Slater GJ, Harmon LJ, Wegmann D, Joyce P, Revell LJ, Alfaro ME. in press Evolution, Leuenberger C, and Wegmann D. 2010. Genetics 184: 243-252., Wegmann D, Leuenberger C, Excoffier L. 2009. Genetics 182: 1207-1218.

Examples

Run this code
# NOT RUN {
example(mecca)
# }

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