get_default_model_options {MOFA2} | R Documentation |
Function to obtain the default model options.
get_default_model_options(object)
object |
an untrained |
This function provides a default set of model options that can be modified and passed to the MOFA
object
in the prepare_mofa
step (see example), i.e. after creating a MOFA
object
(using create_mofa
) and before starting the training (using run_mofa
)
The model options are the following:
likelihoods: character vector with data likelihoods per view: 'gaussian' for continuous data (Default for all views), 'bernoulli' for binary data and 'poisson' for count data.
num_factors: numeric value indicating the (initial) number of factors. Default is 15.
spikeslab_factors: logical indicating whether to use spike and slab sparsity on the factors (Default is FALSE)
spikeslab_weights: logical indicating whether to use spike and slab sparsity on the weights (Default is TRUE)
ard_factors: logical indicating whether to use ARD sparsity on the factors (Default is TRUE only if using multiple groups)
ard_weights: logical indicating whether to use ARD sparsity on the weights (Default is TRUE)
Returns a list with the default model options.
# Using an existing simulated data with two groups and two views file <- system.file("extdata", "test_data.RData", package = "MOFA2") # Load data dt (in data.frame format) load(file) # Create the MOFA object MOFAmodel <- create_mofa(dt) # Load default model options model_opts <- get_default_model_options(MOFAmodel) # Edit some of the model options model_opts$num_factors <- 10 model_opts$spikeslab_weights <- FALSE # Prepare the MOFA object MOFAmodel <- prepare_mofa(MOFAmodel, model_options = model_opts)