nr_iterate: Compute Newton-Raphson Parameter Update with Numerical...

In lgspline: Lagrangian Multiplier Smoothing Splines for Smooth Function Estimation

Compute Newton-Raphson Parameter Update with Numerical Stabilization

Description

Performs parameter update in iterative optimization.

Called by damped_newton_r in the update step

Usage

nr_iterate(gradient_val, neghessian_val)

Arguments

gradient_val	Numeric vector of gradient values (\textbf{u})
neghessian_val	Negative Hessian matrix (\textbf{G}^{-1} approximately)

Details

This helper function is a core component of Newton-Raphson optimization. It provides a computationally-stable approach to computing \textbf{G}\textbf{u}, for information matrix \textbf{G} and score vector \textbf{u}, where the Newton-Raphson update can be expressed as \boldsymbol{\beta}^{(m+1)} = \boldsymbol{\beta}^{(m)} + \textbf{G}\textbf{u}.

Value

Numeric vector of parameter updates (\textbf{G}\textbf{u})

See Also

damped_newton_r for the full optimization routine

lgspline documentation built on June 8, 2025, 10:45 a.m.