pbd_ML {PBD}

Maximization of loglikelihood under protracted birth-death model of diversification

Description

Likelihood maximization for protracted birth-death model of diversification

Usage

pbd_ML(
   brts,
   initparsopt = c(0.2,0.1,1),
   idparsopt = 1:length(initparsopt),
   idparsfix = NULL,
   parsfix = NULL,
   exteq = 1,
   parsfunc = c(function(t,pars) {pars[1]},function(t,pars) {pars[2]},
function(t,pars) {pars[3]}, function(t,pars) {pars[4]}),
   missnumspec = 0,
   cond = 1,
   btorph = 1,
   soc = 2,
   methode = "lsoda",
   n_low = 0,
   n_up = 0,
   tol = c(1E-6, 1E-6, 1E-6),
   maxiter = 1000 * round((1.25)^length(idparsopt)),
   optimmethod = 'subplex',
   verbose = TRUE
)

Arguments

brts

A set of branching times of a phylogeny, all positive

initparsopt

The initial values of the parameters that must be optimized

idparsopt

The ids of the parameters that must be optimized, e.g. 1:4 for all parameters. The ids are defined as follows:
id == 1 corresponds to b (speciation-initiation rate)
id == 2 corresponds to mu_1 (extinction rate of good species)
id == 3 corresponds to la_1 (speciation-completion rate)
id == 4 corresponds to mu_2 (extinction rate of incipient species)

idparsfix

The ids of the parameters that should not be optimized, e.g. c(2,4) if mu_1 and mu_2 should not be optimized, but only b and la_1. In that case idparsopt must be c(1,3).

parsfix

The values of the parameters that should not be optimized

exteq

Sets whether incipient species have the same (1) or different (0) extinction rate as good species. If exteq = 0, then idparsfix and idparsopt should together have all parameters 1:4

parsfunc

Specifies functions how the rates depend on time, default functions are constant functions

missnumspec

The number of species that are in the clade but missing in the phylogeny

cond

Conditioning:
cond == 0 : conditioning on stem or crown age
cond == 1 : conditioning on stem or crown age and non-extinction of the phylogeny
cond == 2 : conditioning on stem or crown age and number of extant taxa

btorph

Sets whether the likelihood is for the branching times (0) or the phylogeny (1)

soc

Sets whether the first element of the branching times is the stem (1) or the crown (2) age

methode

Sets which method should be used in the ode-solver. Default is 'lsoda'. See package deSolve for details.

n_low

Sets the lower bound of the number of species on which conditioning should be done when cond = 2. Set this to 0 when conditioning should be done on precisely the number of species (default)

n_up

Sets the upper bound of the number of species on which conditioning should be done when cond = 2. Set this to 0 when conditioning should be done on precisely the number of species (default)

tol

Sets the tolerances in the optimization. Consists of:
reltolx = relative tolerance of parameter values in optimization
reltolf = relative tolerance of function value in optimization
abstolx = absolute tolerance of parameter values in optimization

maxiter

Sets the maximum number of iterations in the optimization

optimmethod

Method used in optimization of the likelihood. Current default is 'subplex'. Alternative is 'simplex' (default of previous versions)

verbose

if TRUE, explanatory text will be shown

Value

A data frame with the following components:

b

gives the maximum likelihood estimate of b

mu_1

gives the maximum likelihood estimate of mu_1

la_1

gives the maximum likelihood estimate of la_1

mu_2

gives the maximum likelihood estimate of mu_2

loglik

gives the maximum loglikelihood

df

gives the number of estimated parameters, i.e. degrees of feedom

conv

gives a message on convergence of optimization; conv = 0 means convergence

Author(s)

Rampal S. Etienne

See Also

pbd_loglik

Examples

pbd_ML(1:10,initparsopt = c(4.640321,4.366528,0.030521), exteq = 1)