Simulates island replicates with an clade-specific (CS) diversity-dependent constant-rate process
DAISIE_sim_cr_cs(
total_time,
M,
pars,
replicates,
nonoceanic_pars,
prop_type2_pool,
replicates_apply_type2,
sample_freq,
hyper_pars,
area_pars,
cond,
verbose
)A list. The highest level of the least corresponds to each individual replicate. See return for `DAISIE_sim_cr()` for details.
Numeric defining the length of the simulation in time units.
Numeric defining the size of mainland pool, i.e. the number of species that can potentially colonize the island.
A numeric vector containing the model parameters:
pars[1]: lambda^c (cladogenesis rate)
pars[2]: mu (extinction rate)
pars[3]: K (carrying capacity), set K=Inf for diversity
independence.
pars[4]: gamma (immigration rate)
pars[5]: lambda^a (anagenesis rate)
pars[6]: lambda^c (cladogenesis rate) for either type 2 species
or rate set 2 in rate shift model
pars[7]: mu (extinction rate) for either type 2 species or rate
set 2 in rate shift model
pars[8]: K (carrying capacity) for either type 2 species or rate
set 2 in rate shift model, set K=Inf for diversity independence.
pars[9]: gamma (immigration rate) for either type 2 species
or rate set 2 in rate shift model
pars[10]: lambda^a (anagenesis rate) for either type 2
species or rate set 2 in rate shift model
Elements 6:10 are required only when type 2 species are included
or in the rate shift model. For DAISIE_sim_relaxed_rate()
pars[6] is the standard deviation of the gamma distribution for the
relaxed parameter and the parameter chosen by the relaxed_par
argument is the mean of the gamma distribution for the relaxed parameter.
Integer specifying number of island replicates to be simulated.
A vector of length two with:
[1]: the probability of sampling a species from the mainland
[2]: the probability of the species sampled from the mainland being nonendemic
Fraction of mainland species that belongs to the
second subset of species (type 2). Applies only when two types of species
are simulated (length(pars) = 10). For DAISIE_dataprep()
applies only if number_clade_types = 2. In DAISIE_dataprep()
the default "proportional" sets the fraction to be proportional to
the number of clades of distinct macroevolutionary process that have
colonised the island.
Applies only when two types of species are
being simulated. Default replicates_apply_type2 = TRUE runs simulations
until the number of islands where a type 2 species has colonised is equal
to the specified number of replicates. This is recommended if
prop_type2_pool is small or if the rate of immigration of type two
species (pars[9]) is low, meaning that more replicates are needed to
achieved an adequate sample size of islands with type 2 species. Setting
replicates_apply_type2 = FALSE simulates islands up to the
specified number of replicates regardless of whether type 2 species have
colonised or not.
Numeric specifing the number of units times should be divided by for plotting purposes. Larger values will lead to plots with higher resolution, but will also run slower.
A named list of numeric hyperparameters for the rate
calculations as returned by create_hyper_pars():
[1]: is d the scaling parameter for exponent for calculating cladogenesis rate
[2]: is x the exponent for calculating extinction rate
A named list containing area and sea level parameters as
created by create_area_pars():
[1]: maximum area
[2]: current area
[3]: value from 0 to 1 indicating where in the island's history the peak area is achieved
[4]: total island age
[5]: amplitude of area fluctuation from sea level
[6]: frequency of sine wave of area change from sea level
[7]: angle of the slope of the island
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. This last option is not yet available for the IW model
A numeric vector of length 1, which in simulations and `DAISIEdataprep()` can be `1` or `0`, where `1` gives intermediate output should be printed. For ML functions a numeric determining if intermediate output should be printed. The default: `0` does not print, `1` prints the initial likelihood and the settings that were selected (which parameters are to be optimised, fixed or shifted), `2` prints the same as `1 and also the intermediate output of the parameters and loglikelihood, while `3` the same as `2` and prints intermediate progress during likelihood computation.