cpp.airwls.glmstep: Compute one Fisher scoring step for GLMs

In sgdGMF: Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent

Compute one Fisher scoring step for GLMs

Description

Internal function to compute one Fisher scoring step for GLMs. It constitutes the building block of the AIRWLS algorithm for the estimation of GMF models.

Usage

cpp.airwls.glmstep(
  beta,
  y,
  X,
  familyname,
  linkname,
  varfname,
  offset,
  weights,
  penalty
)

Arguments

beta	current value of the regression coefficients to be updated
y	response vector
X	design matrix
familyname	model family name
linkname	link function name
varfname	variance function name
offset	vector of constants to be added to the linear predictor
weights	vector of constants non-negative weights
penalty	penalty parameter of a ridge-type penalty

sgdGMF documentation built on April 3, 2025, 7:37 p.m.