draw_beta_mixture_nsamples: Draw samples from a mixture of beta distributions

In tipmap: Tipping Point Analysis for Bayesian Dynamic Borrowing

Draw samples from a mixture of beta distributions

Description

Draws samples from a mixture of beta distributions, representing pooled weights on the informative component of a robust MAP prior, as elicited from experts via the roulette method.

Usage

draw_beta_mixture_nsamples(n, chips_mult, expert_weight = NULL)

Arguments

n	Numeric value, the number of samples to be drawn.
chips_mult	Numeric matrix, containing expert weighting (distributions of chips). Rows should represent experts, columns should represent bins / weight intervals.
expert_weight	An optional numeric vector, containing the weight assigned to each expert (defaults to equal weights).

Value

A numeric vector containing samples from a pooled distribution of expert opinions.

See Also

fit_beta_mult_exp and get_summary_mult_exp.

Examples

rweights <- draw_beta_mixture_nsamples(
  n = 50,
  chips_mult = rbind(
    c(0, 0, 0, 0, 2, 3, 3, 2, 0, 0),
    c(0, 0, 0, 1, 2, 4, 2, 1, 0, 0),
    c(0, 0, 0, 2, 2, 2, 2, 2, 0, 0)
  ),
  expert_weight = rep(1/3, 3)
)
print(rweights)
## Not run: 
hist(rweights)

## End(Not run)

tipmap documentation built on Aug. 14, 2023, 5:09 p.m.