get_default_model_options {MOFA2} | R Documentation

## Get default model options

### Description

Function to obtain the default model options.

### Usage

    get_default_model_options(object)

### Arguments

`object` | an untrained `MOFA` object

### Details

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)

### Value

Returns a list with the default model options.

### Examples

    # 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)

[Package MOFA2 version 1.0.1 Index]