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. The output is a loglikelihood value
DAISIE_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
)The loglikelihood
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) for an optional
subset of the species
pars1[7] corresponds to mu (extinction rate) for an optional subset of the species
pars1[8] corresponds to K (clade-level carrying capacity) for an optional subset of the
species
pars1[9] corresponds to gamma (immigration rate) for an optional subset of the species
pars1[10] corresponds to lambda^a (anagenesis rate) for an optional subset of the species
pars1[11] corresponds to p_f (fraction of mainland species that belongs to the second
subset of species
The elements 6:10 and 11 are optional, that is, pars1
should either contain 5, 10 or 11 elements. If 10, then the fraction of
potential colonists of type 2 is computed from the data. If 11, then
pars1[11] is used, overruling any information in the data.
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 the level of verbosity. When equal to 0, no output is generated. At higher values
(1 or 2) more output will be generated.
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
or:
$not_present_type1 - the number of mainland lineages of type 1 that are not present on the island
$not_present_type2 - the number of mainland lineages of type 2 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_Singleton_MaxAge: 5
- Endemic_Clade_MaxAge: 6
- Endemic&Non_Endemic_Clade_MaxAge: 7
- Non_endemic_MaxAge_MinAge: 8
- Endemic_Singleton_MaxAge_MinAge: 9
$missing_species - number of island species that were not sampled for
particular clade (only applicable for endemic clades)
$type1or2 - whether the colonist belongs to type 1 or type 2
Method of the ODE-solver. See package deSolve for details. Default is "lsodes"
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
Absolute tolerance of the integration
Relative tolerance of the integration
Rampal S. Etienne & Bart Haegeman
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.
DAISIE_ML, DAISIE_sim_cr,
DAISIE_sim_time_dep,
DAISIE_sim_cr_shift
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)
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