grid_finder {pintervals}R Documentation

Grid search for lower and upper bounds of continuous conformal prediction intervals

Description

Grid search for lower and upper bounds of continuous conformal prediction intervals

Usage

grid_finder(
  y_min,
  y_max,
  ncs,
  ncs_function,
  y_hat,
  alpha,
  min_step = NULL,
  grid_size = NULL,
  return_min_q = FALSE,
  weighted_cp = FALSE,
  calib = NULL
)

Arguments

y_min

minimum value to search

y_max

maximum value to search

ncs

vector of non-conformity scores

ncs_function

a function that takes a vector of predicted values and a vector of true values and returns a vector of non-conformity scores

y_hat

vector of predicted values

alpha

confidence level

min_step

The minimum step size for the grid search

grid_size

Alternative to min_step, the number of points to use in the grid search between the lower and upper bound

return_min_q

logical. If TRUE, the function will return the minimum quantile of the nonconformity scores for each predicted value

weighted_cp

logical. If TRUE, the function will use the weighted conformal prediction method. Default is FALSE

calib

a tibble with the predicted values and the true values of the calibration partition. Used when weighted_cp is TRUE. Default is NULL

Value

a tibble with the predicted values and the lower and upper bounds of the prediction intervals


[Package pintervals version 0.7.7 Index]