fit_P1_precision_L1: Precision-weighted L1 penalty (P1)

In fdb: Frequentist Dynamic Borrowing for Hybrid-Control Survival Trials

Precision-weighted L1 penalty (P1)

Description

Implements p_\lambda(\delta) = \lambda |\delta| / \widehat{SE}(\hat\delta_0), where \widehat{SE}(\hat\delta_0) is the standard error of the unpenalized drift estimator.

Usage

fit_P1_precision_L1(
  dat,
  xnames = NULL,
  lambda,
  delta_bounds = DEFAULT_DELTA_BOUNDS,
  full_fit = NULL,
  robust = FALSE,
  eps = SMOOTH_EPS
)

Arguments

dat	A data frame from simulate_hybrid_cox or conforming to its column conventions.
xnames	Character vector of covariate names. If NULL, automatically detected.
lambda	Penalty strength (\lambda \ge 0).
delta_bounds	Numeric vector of length 2 giving the optimization interval for \delta.
full_fit	Optional pre-computed full Cox fit (output of an internal helper). If NULL, the fit is computed.
robust	Use robust (Lin-Wei) Cox standard errors.
eps	Smoothing parameter for |\delta|_\varepsilon.

Value

A list of estimates and inference quantities, including the effective penalty weight w and the first-stage standard error se_delta.

fdb documentation built on Oct. 4, 2026, 5:07 p.m.