Continuous univariate prior distributions

ContinuousPrior is a sub-class of Prior implementing a generic representation of continuous prior distributions over a compact interval on the real line.

Usage

ContinuousPrior(
  pdf,
  support,
  order = 10,
  label = NA_character_,
  tighten_support = FALSE,
  check_normalization = TRUE
)

Arguments

pdf

vectorized univariate PDF function

support

numeric vector of length two with the bounds of the compact interval on which the pdf is positive.

order

integer, integration order of the employed Gaussian quadrature integration rule to evaluate scores. Automatically set to length(n2_pivots) if
length(n2_pivots) == length(c2_pivots) > 1, otherwise c2 and n2 are taken to be constant in stage-two and replicated to match the number of pivots specified by order

label

object label (string)

tighten_support

logical indicating if the support should be tightened

check_normalization

logical indicating if it should be checked that pdf defines a density.

Slots

pdf

cf. parameter 'pdf'

support

cf. parameter 'support'

pivots

normalized pivots for integration rule (in [-1, 1]) the actual pivots are scaled to the support of the prior

weights

weights of of integration rule at pivots for approximating integrals over delta

See also

Discrete priors are supported via PointMassPrior

Examples

ContinuousPrior(function(x) 2*x, c(0, 1))
#> ContinuousPrior<[0,1]>