Posterior Cost Probability Density.

Calculates the posterior probability density function for costs given observations of risk events.

Usage

cost_post_pdf(
  num_sims,
  observed_risks,
  means_given_risks,
  sds_given_risks,
  base_cost = 0
)

Arguments

num_sims

Number of random samples to draw from the posterior distribution.

observed_risks

A vector of observed values for each risk event 'R_i' (1 if observed, 0 if not observed, NA if unobserved).

means_given_risks

A vector of means of the normal distribution for cost 'A' given each risk event 'R_i'.

sds_given_risks

A vector of standard deviations of the normal distribution for cost 'A' given each risk event 'R_i'.

base_cost

The baseline cost given no risk event occurs.

Value

A numeric vector of random samples from the posterior distribution of costs.

Examples

# Example with three risk events
num_sims <- 1000
observed_risks <- c(1, NA, 1)
means_given_risks <- c(10000, 15000, 5000)
sds_given_risks <- c(2000, 1000, 1000)
base_cost <- 2000
posterior_samples <- cost_post_pdf(
  num_sims = num_sims,
  observed_risks = observed_risks,
  means_given_risks = means_given_risks,
  sds_given_risks = sds_given_risks,
  base_cost = base_cost
)
hist(posterior_samples, breaks = 30, col = "skyblue", main = "Posterior Cost PDF", xlab = "Cost")