transformPhylo.ll: Log-likelhood for models of trait evolution.

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/transformPhylo.ll.R

Description

Fits likelihood models for various models of continuous character evolution.

Usage

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transformPhylo.ll(
  y = NULL,
  phy,
  model = NULL,
  meserr = NULL,
  kappa = NULL,
  lambda = NULL,
  delta = NULL,
  alpha = NULL,
  psi = NULL,
  lambda.sp = NULL,
  nodeIDs = NULL,
  rateType = NULL,
  branchRates = NULL,
  cladeRates = NULL,
  timeRates = NULL,
  splitTime = NULL,
  branchLabels = NULL,
  acdcRate = NULL,
  covPIC = TRUE,
  cophenetic.dist = NULL,
  vcv.matrix = NULL,
  mode.order = NULL,
  mode.param = NULL,
  rate.var = NULL,
  mu = NULL,
  sigma.sq = NULL
)

Arguments

y

A matrix of trait values.

phy

An object of class phylo (see ape).

model

The model of trait evolution (see details).

meserr

A vector (or matrix) of measurement error for each tip. This is only applicable to univariate analyses.

kappa

Value of kappa transform.

lambda

Value of lambda transform.

delta

Value of delta transform.

alpha

Value of alpha (OU) transform.

psi

Value of psi transform.

lambda.sp

Speciation rate estimate for the tree.

nodeIDs

Integer - ancestral nodes of clades.

rateType

If model="clade", a vector specifying if rate shift occurs in a clade ("clade") or on the single branch leading to a clade ("branch").

branchRates

Numeric vector specifying relative rates for individual branches

cladeRates

Numeric vector specifying relative rates for clades or logical to indicate scalar is included in the 'modeslice' model (the scalar value is included in the mode.param argument with the 'modeslice' model).

timeRates

The rates (from ancient to recent) for the timeSlice model

splitTime

A split time (measured from the present, or most recent species) at which a shift in the rate occurs for the "timeSlice" model

branchLabels

Branches on which different psi parameters are estimated in the "multipsi" model.

acdcRate

Value of ACDC transform

covPIC

Logical. For multivariate analyses, allow for co-variance between traits rates (TRUE) or no covariance in trait rates (FALSE). If FALSE, only the trait variances not co-variances are used.

cophenetic.dist

a cophenetic distance matrix showing the absolute distance between taxa - only applicable for OU models run on non-ultrmetric trees. If null will be calculated internally, but supplying the data can speed up run time

vcv.matrix

a variance-covariance matrix - only applicable for OU models run on non-ultrmetric trees. If null will be calculated internally, but supplying the data can speed up run time

mode.order

The order of modes for the 'modeslice' model. Any combination of 'BM', 'OU', 'acdc', and 'kappa'

mode.param

Parameters for the modes of evoluton in the 'modeslice' model

rate.var

Allows rate variation in BM modes in the 'modeslice' model

mu

Phylogenetic mean estimate, Mainly for internal use when using the variance-covariance method to calculate likelihood for non-ultrametric trees with the OU model

sigma.sq

Brownian variance estimate, mainly for internal use when using the variance-covariance method to calculate likelihood for non-ultrametric trees with the OU model

Details

This function fits likelihood models (see below) for continuous character evolution where the parameter values are set a priori. The function returns the log-likihood and the Brownian variance (or variance covariance matrix).

Value

brownianVariance Brownian variance (or covariance for multiple traits) given the data and phylogeny

logLikelihood The log-likelihood of the model and data

Author(s)

Gavin Thomas, Mark Puttick

References

Felsenstein J. 1973. Maximum-likelihood estimation of evolutionary trees from continuous characters. Am. J. Hum. Genet. 25, 471-492. Felsenstein J. 1985. Phylogenies and the comparative method. American Naturalist 125, 1-15. Freckleton RP & Jetz W. 2009. Space versus phylogeny: disentangling phylogenetic and spatial signals in comparative data. Proc. Roy. Soc. B 276, 21-30.

Ingram T. 2011. Speciation along a depth gradient in a marine adaptive radiation. Proc. Roy. Soc. B. 278, 613-618.

Ingram T, Harrison AD, Mahler L, Castaneda MdR, Glor RE, Herrel A, Stuart YE, and Losos JB. 2016. Comparative tests of the role of dewlap size in Anolis lizard speciation. Proc. Roy. Soc. B. 283, 20162199. #' Mooers AO, Vamosi S, & Schluter D. 1999. Using phylogenies to test macroevolutionary models of trait evolution: sexual selection and speciation in Cranes (Gruinae). American Naturalist 154, 249-259. O'Meara BC, Ane C, Sanderson MJ & Wainwright PC. 2006. Testing for different rates of continuous trait evolution using likelihood. Evolution 60, 922-933 Pagel M. 1997. Inferring evolutionary processes from phylogenies. Zoologica Scripta 26, 331-348. Pagel M. 1999 Inferring the historical patterns of biological evolution. Nature 401, 877-884. Thomas GH, Meiri S, & Phillimore AB. 2009. Body size diversification in Anolis: novel environments and island effects. Evolution 63, 2017-2030.

See Also

transformPhylo.ML,transformPhylo.MCMC, transformPhylo.sim

Examples

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# Data and phylogeny
data(anolis.tree)
data(anolis.data)

# anolis.data is not matrix and contains missing data so put together matrix of
# relevant traits (here female and male snout vent lengths) and remove species 
# with missing data from the matrix and phylogeny
sorted.traits <- sortTraitData(anolis.tree, anolis.data,
c("Female_SVL", "Male_SVL"), log.trait=TRUE, pass.ultrametric=TRUE)

tree <- sorted.traits$phy
traits <- sorted.traits$trait

# log likelihood of kappa = 0.1 or 1
transformPhylo.ll(traits, phy=tree, model="kappa", kappa=0.1)
transformPhylo.ll(traits, phy=tree, model="kappa", kappa=1)

# log likelihood of lambda = 0.01 or 1
transformPhylo.ll(traits, phy=tree, model="lambda", lambda=0.01)
transformPhylo.ll(traits, phy=tree, model="lambda", lambda=1)

# log likelihood of delta = 1.5 or 1
transformPhylo.ll(traits, phy=tree, model="delta", delta=1.5)
transformPhylo.ll(traits, phy=tree, model="delta", delta=1)

# log likelihood of alpha = 0.001 or 2
transformPhylo.ll(traits, phy=tree, model="OU", alpha=0.001)
transformPhylo.ll(traits, phy=tree, model="OU", alpha=2)

PuttickMacroevolution/motmot documentation built on June 5, 2020, 7 p.m.