create_inference_model {beautier} | R Documentation |
Create a Bayesian phylogenetic inference model, as can be done by BEAUti.
create_inference_model(
site_model = create_jc69_site_model(),
clock_model = create_strict_clock_model(),
tree_prior = create_yule_tree_prior(),
mrca_prior = NA,
mcmc = create_mcmc(),
beauti_options = create_beauti_options(),
tipdates_filename = NA
)
site_model |
a site model,
as returned by |
clock_model |
a clock model,
as returned by |
tree_prior |
a tree priors,
as returned by |
mrca_prior |
a Most Recent Common Ancestor prior,
as returned by |
mcmc |
one MCMC.
Use |
beauti_options |
one BEAUti options object,
as returned by |
tipdates_filename |
name of the file containing the tip dates. This file is assumed to have two columns, separated by a tab. The first column contains the taxa names, the second column contains the date. |
an inference model
RichÃ¨l J.C. Bilderbeek
Use create_test_inference_model to create an inference model with a short MCMC, to be used in testing. Use create_ns_inference_model to create an inference model to estimate the marginal likelihood (aka evidence) using a nested sampling approach.
if (is_on_ci()) {
check_empty_beautier_folder()
# Create an MCMC chain with 50 states
inference_model <- create_inference_model(
mcmc = create_mcmc(chain_length = 50000, store_every = 1000)
)
output_filename <- get_beautier_tempfilename()
create_beast2_input_file_from_model(
input_filename = get_fasta_filename(),
output_filename = output_filename,
inference_model = inference_model
)
file.remove(output_filename)
remove_beautier_folder()
check_empty_beautier_folder()
}