motmot (version 2.1.3)

ML.RatePhylo: Maximum likelihood rate estimation for traits and phylogenies

Description

Full function for maximum likelihood estimation of rate parameters and comparison to a single rate model.

Usage

ML.RatePhylo(
  rateData,
  rate = NULL,
  fixed = NULL,
  pretty = TRUE,
  rateMIN = 0.001,
  rateMAX = 50,
  common.mean = FALSE,
  lambda.est = TRUE,
  est.CI = FALSE,
  meserr = FALSE,
  file = NULL
)

Arguments

rateData

an object of class rateData

rate

a vector of relative rate parameters. The length of the vector is equal to the number of rates being estimated. If rate=NULL then rates are equal.

fixed

A vector stating whether each parameter should be allowed to vary (either FALSE which results in a start value of 1, or a numeric start value) or should be fixed (TRUE).

pretty

Display the output nicely (pretty=TRUE) or as a list (pretty=FALSE)

rateMIN

Minimum value for the rate parameters.

rateMAX

Maximum value for the rate parameters

common.mean

a logical specififying whether each rate category should have its own mean (common.mean=FALSE) or all categories should have the same mean (common.mean=TRUE). See Thomas et al. (2009) for a discussion on the impact of assumptions about mean on rate estimates.

lambda.est

Logical. Estimate Pagel's lambda.

est.CI

Logical. Estimate approximate confidence intervals for rate parameters.

meserr

Logical. Incorporate measurement error.

file

File string for output. Only used if pretty=TRUE.

Value

If pretty=FALSE, returns a list containing:

• MLRate Maximum likelihood estimates of the rate parameters

• Lambda Maximum likelihood estimate of lambda

• LCI Approximate lower confidence intervals for rate

• UCI Approximate upper confidence intervals for rate parameters

• means Means for each category

• nParam Number of parameters in the model (how many means and rate categories)

• Max.lik Maximum (log) likeihood

• AIC for maximum likelihood model

• AICc for maximum likelihood model

• LambdaSingle Maximum likelihood estimate of lambda for the single rate model

• Lik1 Likelihood of the equivalent single rate model

• Likelihood ratio statistic of "Max.lik" vs "Lik1"

• P P values for the LR statistic

• df Degrees of freedom for the LR statistic

• AIC.rate1 AIC for single rate model

• AICc.rate1 AICc for single rate model

If pretty=TRUE, prints a nice version of the list to screen. If file is specified the pretty output will be sent to file, not the console.

References

Thomas GH, Freckleton RP, & Szekely T. 2006. Comparative analyses of the influence of developmental mode on phenotypic diversification rates in shorebirds. Proceedings of the Royal Society B 273, 1619-1624.

Thomas GH, Meiri S, & Phillimore AB. 2009. Body size diversification in Anolis: novel environments and island effects. Evolution 63, 2017-2030.

Examples

# NOT RUN {
## Read in phylogeny and data from Thomas et al. (2009)
data(anolis.tree)
data(anolis.data)
## Convert data to class rateData with a rateMatrix object as input
anolis.rateMatrix <- as.rateMatrix(phy=anolis.tree, x="geo_ecomorph",
data=anolis.data)
anolis.rateData <- as.rateData(y="Female_SVL", x="geo_ecomorph", 
rateMatrix = anolis.rateMatrix, phy=NULL, data=anolis.data, log.y=TRUE)
# A model with a different rate in one of the four groups. The 'fixed' command is used to determine
# whether a particular rate is to be constrained or not. Use '1' to fix a group and 'FALSE' to show
# that the parameter is not fixed and should be estimated. The values should be entered in the same 
# order as the ranking of the groups. That is, group 0 (small islands) takes position one in the 
# fixed vector, group 1 (large island trunk crown and trunk ground) takes position 2 and so on. 
# The default is to allow each group to take a different mean. 
ML.RatePhylo(anolis.rateData, fixed=c(1, FALSE, FALSE, FALSE), pretty=TRUE, lambda.est = FALSE)
# }

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