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