• select performs strict selection, returning either TRUE or FALSE for each component.

• select.integrate is like select, but instead of a fixed threshold, computes probabilistic selection by integrating over a threshold density.

• select_freq performs the selection separately using each parameter draw and returns the frequency at which each component was selected.

• select_freq.integrate is like select_freq, but instead of a fixed threshold, computes probabilistic selection frequencies by integrating over a threshold density.

select(fit, reduce = function(x) base::mean(x), threshold = 0.95, ...)

select_freq(fit, threshold = 0.95, ...)

select.integrate(
fit,
reduce = function(x) base::mean(x),
p = function(x) stats::dbeta(x, 100, 5),
h = 0.01,
verbose = TRUE,
...
)

select_freq.integrate(
fit,
p = function(x) stats::dbeta(x, 100, 5),
h = 0.01,
verbose = TRUE,
...
)

## Arguments

fit An object of class lgpfit. The reduce argument for relevances. Threshold for relevance sum. Must be a value between 0 and 1. Additional arguments to relevances. A threshold density over interval [0,1]. A discretization parameter for computing a quadrature. Should this show a progress bar?

See description.