Predict method for conformalize objects — predict.conformalize • misc

This function generates prediction intervals for new data using the fitted conformal model.

# S3 method for class 'conformalize'
predict(
  object,
  newdata,
  predict_func = predict,
  level = 0.95,
  method = c("splitconformal", "kde", "surrogate", "bootstrap"),
  n_sim = 250L,
  seed = 123L,
  ...
)

Arguments

object: A conformalize object.
newdata: A data frame or matrix of new data for prediction.
level: The confidence level for the prediction intervals. Default is 0.95.
method: The method to use for prediction intervals. Options are "split" or "simulation".
n_sim: The number of simulations to perform if using the "simulation" method. Default is 1000.
seed: An optional seed for reproducibility.
...: Additional arguments to pass to the predict function.

Value

A matrix with predictions and prediction intervals.

Examples


if (FALSE) { # \dontrun{
# Define fit and predict functions
fit_func <- function(formula, data, ...) stats::glm(formula, data = data, ...)
predict_func <- function(fit, newdata, ...) predict(fit, newdata, ...)

# Apply conformalize using the training data
conformal_model_boston <- misc::conformalize(
  formula = medv ~ .,
  data = train_data,
  fit_func = fit_func,
  predict_func = predict_func,
  seed = 123
)

# Predict with split conformal method on the test data
predictions_boston <- predict(
  conformal_model_boston,
  newdata = test_data,
  level = 0.95,
  method = "split"
)

head(predictions_boston)
} # }