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Computes the loglikelihood of the DAISIE model with clade-specific diversity-dependence given data and a set of model parameters that may shift at some time

Source: R/DAISIE_SR_loglik_CS.R
DAISIE_SR_loglik_CS.Rd

Computes the loglikelihood of the DAISIE model with clade-specific diversity-dependence given colonization and branching times for lineages on an island, and a set of model parameters that may shift at some time

Usage

DAISIE_SR_loglik_CS(
  pars1,
  pars2,
  datalist,
  methode = "odeint::runge_kutta_cash_karp54",
  CS_version = list(model = 1, function_to_optimize = "DAISIE"),
  abstolint = 1e-16,
  reltolint = 1e-10
)

Arguments

pars1

Contains the model parameters:

pars1[1] corresponds to lambda^c (cladogenesis rate)
pars1[2] corresponds to mu (extinction rate)
pars1[3] corresponds to K (clade-level carrying capacity)
pars1[4] corresponds to gamma (immigration rate)
pars1[5] corresponds to lambda^a (anagenesis rate)
pars1[6] corresponds to lambda^c (cladogenesis rate) after the shift
pars1[7] corresponds to mu (extinction rate) after the shift
pars1[8] corresponds to K (clade-level carrying capacity) after the shift
pars1[9] corresponds to gamma (immigration rate) after the shift
pars1[10] corresponds to lambda^a (anagenesis rate) after the shift
pars1[11] corresponds to the time of shift

pars2

Contains the model settings

pars2[1] corresponds to lx = length of ODE variable x
pars2[2] corresponds to ddmodel = diversity-dependent model, model of diversity-dependence, which can be one of

ddmodel = 0 : no diversity dependence
ddmodel = 1 : linear dependence in speciation rate
ddmodel = 11: linear dependence in speciation rate and in immigration rate
ddmodel = 2 : exponential dependence in speciation rate
ddmodel = 21: exponential dependence in speciation rate and in immigration rate

pars2[3] corresponds to cond = setting of conditioning

cond = 0 : conditioning on island age
cond = 1 : conditioning on island age and non-extinction of the island biota
cond > 1 : conditioning on island age and having at least cond colonizations on the island

pars2[4] sets whether parameters and likelihood should be printed (1) or not (0)

datalist

Data object containing information on colonisation and branching times. This object can be generated using the DAISIE_dataprep function, which converts a user-specified data table into a data object, but the object can of course also be entered directly. It is an R list object with the following elements.
The first element of the list has two or three components:

$island_age - the island age
Then, depending on whether a distinction between types is made, we have:
$not_present - the number of mainland lineages that are not present on the island
The remaining elements of the list each contains information on a single colonist lineage on the island and has 5 components:

$colonist_name - the name of the species or clade that colonized the island
$branching_times - island age and stem age of the population/species in the case of Non-endemic, Non-endemic_MaxAge and Endemic anagenetic species. For cladogenetic species these should be island age and branching times of the radiation including the stem age of the radiation.
$stac - the status of the colonist

- Non_endemic_MaxAge: 1
* Endemic: 2
- Endemic&Non_Endemic: 3
- Non_endemic: 4
- Endemic_MaxAge: 5

$missing_species - number of island species that were not sampled for particular clade (only applicable for endemic clades)

methode

Method of the ODE-solver. See package deSolve for details. Default is "lsodes"

CS_version

a numeric or list. Default is CS_version = list(model = 1, function_to_optimize = 'DAISIE'), but for a relaxed-rate model the list can contain more elements:

  • model: the CS model to run, options are 1 for single rate DAISIE model, 2 for multi-rate DAISIE, or 0 for IW test model

  • function_to_optimize: the DAISIE loglikelihood function that will be optimized. Options are: "DAISIE", default, the full DAISIE loglikelihood "DAISIE_approx", an approximate loglikelihood "DAISIE_DE", an exact loglikelkhood for K = Inf based on the D-E approach

  • integration_method: the method used to do integraion in the relaxed rate model. Options are: 'standard' the default numerical integration 'MC' Monte Carlo integration 'stratified' using quantiles of the gamma distribution

  • relaxed_par: the parameter to relax (integrate over) in the relaxed rate model. Options are "cladogenesis", "extinction", "carrying_capacity", "immigration", or "anagenesis"

  • par_sd: standard deviation of the parameter to relax

  • par_upper_bound upper bound of the parameter to relax

  • seed: seed of the random number generator in case of 'MC'

  • sample_size: size of sample in case of 'MC' or 'stratified'

  • parallel: use parallel computing or not in case of 'MC' or 'stratified'

  • n_cores: number of cores to use when run in parallel

abstolint

Absolute tolerance of the integration

reltolint

Relative tolerance of the integration

Value

The loglikelihood

Details

The output is a loglikelihood value

References

Valente, L.M., A.B. Phillimore and R.S. Etienne (2015). Equilibrium and non-equilibrium dynamics simultaneously operate in the Galapagos islands. Ecology Letters 18: 844-852.

See also

DAISIE_ML, DAISIE_sim_cr

Author

Rampal S. Etienne & Bart Haegeman

Examples


utils::data(Galapagos_datalist_2types)
pars1 = c(0.195442017,0.087959583,Inf,0.002247364,0.873605049,
          3755.202241,8.909285094,14.99999923,0.002247364,0.873605049,0.163)
pars2 = c(100,11,0,1)
DAISIE_loglik_all(pars1,pars2,Galapagos_datalist_2types)
#> High lambda detected; approximation used.
#> High lambda detected; approximation used.
#> [1] -61.70372