Bayesian PCA parameters — prior_slab

A numeric parameter function representing parameters for the spike-and-slab prior used by embed::step_pca_sparse_bayes().

Usage

prior_slab_dispersion(range = c(-1/2, log10(3)), trans = transform_log10())

prior_mixture_threshold(range = c(0, 1), trans = NULL)

Arguments

range: A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units.
trans: A trans object from the scales package, such as scales::transform_log10() or scales::transform_reciprocal(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

Details

prior_slab_dispersion() is related to the prior for the case where a PCA loading is selected (i.e. non-zero). Smaller values result in an increase in zero coefficients.

prior_mixture_threshold() is used to threshold the prior to determine which parameters are non-zero or zero. Increasing this parameter increases the number of zero coefficients.

Examples

mixture()
#> Proportion of Lasso Penalty (quantitative)
#> Range: [0, 1]