Computes the log probability of no species present under the DAISIE model with clade-specific diversity-dependence. The output is a log value.
DAISIE_logp0(
pars1,
pars2,
island_age,
methode = "odeint::runge_kutta_cash_karp54",
CS_version = list(model = 1, function_to_optimize = "DAISIE"),
abstolint = 1e-16,
reltolint = 1e-10
)
The logarithm of the probability
Vector of 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).
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
the island age
Method of the ODE-solver. Supported Boost ODEINT
solvers (steppers) are:
"odeint::runge_kutta_cash_karp54"
"odeint::runge_kutta_fehlberg78"
"odeint::runge_kutta_dopri5"
"odeint::bulirsch_stoer"
without odeint::
-prefix, ode
method is
assumed. The default method overall is
"lsodes"
for DAISIE_ML_CS()
and "ode45"
from ode()
for
DAISIE_ML_IW()
.
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
Numeric absolute tolerance of the integration
Numeric relative tolerance of the integration
Rampal S. Etienne & Bart Haegeman