level_set: Grid-based level-set utilities

In debiasedInference: Bootstrap Inference with Debiased Nonparametric Estimators

Grid-based level-set utilities

Description

Estimate equality level sets on a one-dimensional or rectangular two- dimensional grid, invert a simultaneous band to obtain a confidence set, or calculate finite-point-cloud Hausdorff distance.

Usage

level_set(estimate, level)

invert_confidence_band(band, level)

hausdorff_distance(a, b)

density_level_set(x, level, points = NULL, bandwidth = NULL, tau = 1,
  grid_size = 200L)

density_level_set_confidence(x, level, points = NULL, bandwidth = NULL,
  tau = 1, confidence = 0.95, n_boot = 999L, method = "hausdorff",
  random_state = NULL, grid_size = 200L, max_attempts = NULL)

inverse_regression(x, y, level, points = NULL, bandwidth = NULL,
  tau = 1, grid_size = 200L, n_folds = 5L, random_state = 0L)

inverse_regression_confidence(x, y, level, points = NULL,
  bandwidth = NULL, tau = 1, confidence = 0.95, n_boot = 999L,
  method = "hausdorff", random_state = NULL, grid_size = 200L,
  n_folds = 5L, max_attempts = NULL)

Arguments

estimate	A di_estimate object.
band	A di_band object.
level	Finite target level.
a	First non-empty numeric vector or point matrix.
b	Second non-empty numeric vector or point matrix.
x	Numeric observations or covariates.
y	Numeric responses for inverse regression.
points	Optional evaluation grid. Density level sets accept a vector or a complete rectangular two-dimensional point matrix; inverse regression accepts a vector.
bandwidth	Optional positive bandwidth.
tau	Positive ratio h/b.
grid_size	Generated grid size when points are omitted.
confidence	Confidence level strictly between zero and one.
n_boot	Positive number of bootstrap replicates.
method	Either "hausdorff" or "inversion"; inverse regression additionally supports "normal" for a unique crossing.
random_state	Optional local random seed.
max_attempts	Maximum resamples attempted when sets are empty.
n_folds	Cross-validation folds for a regression bandwidth.

Value

Level-set and inverse-regression functions return a di_set; hausdorff_distance() returns a nonnegative scalar.

debiasedInference documentation built on Sept. 29, 2026, 5:09 p.m.