Implements a Newton-Raphson step to update the regression parameter beta
using the partial derivatives of the log-likelihood. Internally calls helper
functions for computing the score and information matrix components (e.g. xi1G.f).
Arguments
- Hf
A list of functions
(H, H1, H2)defining the baseline hazard (or similar).- beta
Numeric vector of regression coefficients (initial/current guess).
- y
Numeric vector of baseline-related parameters (often updated by
profile1).- delta, gamma
Numeric 0/1 vectors indicating left and interval censoring status.
- index
A 2-column integer matrix mapping each subject's interval to indices in
y.- Z
A matrix or data frame of covariates.
- eps
Convergence tolerance for updating
beta.- maxiter
Maximum number of Newton-Raphson iterations.