Creates the list object for CS_version argument in DAISIE_ML_CS
create_CS_version(
model = 1,
function_to_optimize = "DAISIE",
relaxed_par = NULL,
par_sd = 0,
par_upper_bound = Inf,
integration_method = "standard",
seed = 42,
sample_size = 100,
parallel = FALSE,
n_cores = 1
)
A list of four 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
fumction_to_optimize likelihood function that must be optimized in ML, either 'DAISIE', 'DAISIE_approx', or 'DAISIE_DE'
relaxed_par: the parameter to relax (integrate over), for model = 2.
par_sd: the standard deviation of the parameter to relax
par_upperbound: upper bound of the parameter to relax.
integration_method: method of integration, either 'standard', 'stratified' or 'MC'
seed: random seed in case of integration_method = 'MC'
sample_size: size of sample in case of integration_method = 'MC' or 'stratified'
parallel: use parallel computing or not in case of integration_method = 'MC' or 'stratified'
n_cores: number of cores to use when run in parallel
the CS model to run, options are 1
for single rate
DAISIE model, 2
for multi-rate DAISIE, or 0
for IW test
model
likelihood function that must be optimized in ML, either 'DAISIE', 'DAISIE_approx', or 'DAISIE_DE'
the parameter to relax (integrate over). Options are
"cladogenesis"
,
"extinction"
,
"carrying_capacity"
,
"immigration"
,
"anagenesis"
standard deviation of the parameter to relax
upper bound of the parameter to relax
method of integration, either 'standard','stratified' or 'MC'
seed of the random number generator in case of 'MC'
size of sample in case of 'MC' or 'stratified'
use parallel computing or not in case of 'MC' or 'stratified'
number of cores to use when run in parallel