This function generates random samples from the posterior distribution of the cost 'A' given observations of multiple risk events 'R_i'. Each risk event has its own mean and standard deviation for the cost distribution. The function also accounts for a baseline cost when no risk event occurs.
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.
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")
