se1: MDYPL state evolution functions with intercept

In brglm2: Bias Reduction in Generalized Linear Models

MDYPL state evolution functions with intercept

Description

MDYPL state evolution functions with intercept

Usage

se1(
  mu,
  b,
  sigma,
  iota,
  kappa,
  gamma,
  alpha,
  intercept,
  gh = NULL,
  prox_tol = 1e-10
)

Arguments

mu	aggregate bias parameter.
b	parameter b in the state evolution functions.
sigma	square root of the aggregate variance of the MDYPL estimator.
iota	limits of the MDYPL estimate for the intercept as the sample size goes to +Inf
kappa	asymptotic ratio of columns/rows of the design matrix. kappa should be in ⁠(0, 1)⁠.
gamma	the square root of the limit of the variance of the linear predictor.
alpha	the shrinkage parameter of the MDYPL estimator. alpha should be in ⁠(0, 1)⁠.
intercept	intercept of the logistic regression model
gh	A list with the Gauss-Hermite quadrature nodes and weights, as returned from statmod::gauss.quad() with kind = "hermite". Default is NULL, in which case gh is set to statmod::gauss.quad(200, kind = "hermite") is used.
prox_tol	tolerance for the computation of the proximal operator; default is 1e-10. fixed point problem solved via Newton-Raphson

brglm2 documentation built on Aug. 29, 2025, 5:25 p.m.