`R/create_inference_model.R`

`create_inference_model.Rd`

Create a Bayesian phylogenetic inference model, as can be done by BEAUti.

```
create_inference_model(
site_model = beautier::create_jc69_site_model(),
clock_model = beautier::create_strict_clock_model(),
tree_prior = beautier::create_yule_tree_prior(),
mrca_prior = NA,
mcmc = beautier::create_mcmc(),
beauti_options = beautier::create_beauti_options(),
tipdates_filename = NA
)
```

- site_model
a site model, as returned by

`create_site_model`

- clock_model
a clock model, as returned by

`create_clock_model`

- tree_prior
a tree priors, as returned by

`create_tree_prior`

- mrca_prior
a Most Recent Common Ancestor prior, as returned by

`create_mrca_prior`

- mcmc
one MCMC. Use

`create_mcmc`

to create an MCMC. Use`create_ns_mcmc`

to create an MCMC for a Nested Sampling run. Use`check_mcmc`

to check if an MCMC is valid. Use`rename_mcmc_filenames`

to rename the filenames in an MCMC.- beauti_options
one BEAUti options object, as returned by

`create_beauti_options`

- 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

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.

```
# 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)
#> [1] TRUE
```