pbd_ML: Maximization of loglikelihood under protracted birth-death...
In PBD: Protracted Birth-Death Model of Diversification

Description Usage Arguments Value Author(s) See Also Examples

Likelihood maximization for protracted birth-death model of diversification

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
)

`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

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