create_CS_version | R Documentation |
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
)
model |
the CS model to run, options are |
function_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). Options are
|
par_sd |
standard deviation of the parameter to relax |
par_upper_bound |
upper bound of the parameter to relax |
integration_method |
method of integration, either 'standard','stratified' or 'MC' |
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 |
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
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