EVPI (Expected Value of Perfect Information) for validation Takes a vector of mean and a 2X2 covariance matrix — evpi_val • predtools

EVPI (Expected Value of Perfect Information) for validation Takes a vector of mean and a 2X2 covariance matrix

evpi_val(
  Y,
  pi,
  method = c("bootstrap", "bayesian_bootstrap", "asymptotic"),
  n_sim = 1000,
  zs = (0:99)/100,
  weights = NULL
)

Arguments

Y: Binary response variable
pi: Mean of the second distribution
method: EVPI calculation method
n_sim: Number of Monte Carlo simulations (for bootstrap-based methods)
zs: vector of risk thresholds at which EVPI is to be calculated
weights: (optional) observation weights

Value

Returns a data frame containing thresholds, EVPIs, and some auxilary output.