debias_standard: Standard debiasing

In dScoreTest: Debiased Score Tests for Goodness of Fit and Model Comparison

Standard debiasing

Description

Transform a hunted function \hat{h} into a debiased function \hat{h} - \hat{m}_{\hat{h}}, where \hat{m}_{\hat{h}} is the projection of \hat{h} onto the null model.

Usage

debias_standard(
  h.hat,
  X.debias,
  fit.debias,
  predict_fun,
  weight_fun,
  wls_method,
  arg.wls_method
)

Arguments

h.hat	A list as returned by one of hunt_optimal(), hunt_wls(), hunt_vanilla().
X.debias	Part of X for debiasing.
fit.debias	Null model fitted on the debiasing sample of X and y.
predict_fun, weight_fun, wls_method, arg.wls_method	They must be compatible with fit.debias; see dScoreTest() for details.

Details

The projection \hat{m}_{\hat{h}} is obtained by fitting the null model (via wls_method, weighted by weight_fun(fit.debias, X.debias)) with the hunted values h.hat$h(X.debias) as response. This projection uses all columns of X, even when the hunt itself is driven by only a subset of covariates (h.hat$X.cols).

Value

A list with elements:

m.h.fit

The null model fitted (over all columns of X) to project and debias \hat{h}.

h

The debiased hunt function \hat{h} - \hat{m}_{\hat{h}} with signature h(X).

dScoreTest documentation built on Sept. 3, 2026, 1:06 a.m.