DAMOCLES_ML: Maximization of the loglikelihood under the DAMOCLES model

In rsetienne/DAMOCLES: Dynamic Assembly Model of Colonization, Local Extinction and Speciation

Description

This function computes the maximum likelihood estimates of the parameters of the DAMOCLES model for a given phylogeny and presence-absence data. It also outputs the corresponding loglikelihood that can be used in model comparisons.

Usage

DAMOCLES_ML(
  phy,
  pa,
  initparsopt,
  idparsopt = 1:length(initparsopt),
  parsfix = NULL,
  idparsfix = NULL,
  idparsequal = NULL,
  pars2 = c(0.001, 1e-04, 1e-05, 1000),
  optimmethod = "subplex",
  pchoice = 0,
  edgeTList = NULL,
  methode = "analytical",
  model = 0,
  verbose = FALSE
)

Arguments

phy	phylogeny in phylo format
pa	presence-absence table. The first column contains the labels of the species (corresponding to the tip labels in the phylogeny. The second column contains the presence (1) or absence (0) of species in the local community.
initparsopt	The initial values of the parameters that must be optimized
idparsopt	The ids of the parameters that must be optimized, e.g. 1:2 for extinction rate, and offset of immigration rate The ids are defined as follows: id == 1 corresponds to mu (extinction rate) id == 2 corresponds to gamma_0 (offset of immigration rate) id == 3 corresponds to gamma_1 (parameter controlling decline in immigration rate with time)
parsfix	The values of the parameters that should not be optimized. See idparsfix.
idparsfix	The ids of the parameters that should not be optimized, e.g. c(1,3) if mu and gamma_1 should not be optimized, but only gamma_0. In that case idparsopt must be c(2). The default is to fix all parameters not specified in idparsopt.
idparsequal	The ids of the parameters that should be set equal to the first parameter of the same type.
pars2	Vector of settings: pars2[1] sets the relative tolerance in the parameters pars2[2] sets the relative tolerance in the function pars2[3] sets the absolute tolerance in the parameters pars2[4] sets the maximum number of iterations
optimmethod	Method used in optimization of the likelihood. Current default is 'subplex'. Alternative is 'simplex' (default of previous version)
pchoice	sets the p-value to optimize: pchoice == 0 corresponds to the sum of p_0f + p_1f pchoice == 1 corresponds to p_0f pchoice == 2 corresponds to p_1f
edgeTList	list of edge lengths that need to be succesively pruned; if not specified, it will computed using compute_edgeTList
methode	method used to solve the ODE. Either 'analytical' for the analytical solution, 'Matrix' for matrix exponentiation using package Matrix or 'expm' using package 'expm' or any of the numerical solvers, used in deSolve.
model	model used. Default is 0 (standard null model). Other options are 1 (binary traits) 2 (trinary environmental trait) or 3 (diversity-dependent colonization - beta version)
verbose	Whether intermediate output should be printed. Default is FALSE.

Details

The output is a dataframe containing estimated parameters and maximum loglikelihood.

Value

mu	gives the maximum likelihood estimate of mu
gamma_0	gives the maximum likelihood estimate of gamma_0
gamma_1	gives the maximum likelihood estimate of gamma_1
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

References

Pigot, A.L. & R.S. Etienne (2015). A new dynamic null model for phylogenetic community structure. Ecology Letters 18: 153-163.

See Also

DAMOCLES_loglik DAMOCLES_sim

rsetienne/DAMOCLES documentation built on Feb. 8, 2021, 1:35 p.m.