prior_slab_dispersion: Bayesian PCA parameters

Description Usage Arguments Details Examples

View source: R/param_sparse_bayes_pca.R

Description

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

Usage

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prior_slab_dispersion(range = c(-1/2, log10(3)), trans = log10_trans())

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.

trans

A trans object from the scales package, such as scales::log10_trans() or scales::reciprocal_trans(). 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

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Example output

Loading required package: scales
Proportion of lasso Penalty (quantitative)
Range: [0, 1]

dials documentation built on Sept. 10, 2021, 5:06 p.m.