damped_newton_r {lgspline} | R Documentation |
Damped Newton-Raphson Parameter Optimization
Description
Performs iterative parameter estimation with adaptive step-size dampening
Internal function for fitting unconstrained GLM models using damped Newton-Raphson optimization technique.
Usage
damped_newton_r(
parameters,
loglikelihood,
gradient,
neghessian,
tol = 1e-07,
max_cnt = 64,
max_dmp_steps = 16
)
Arguments
parameters |
Initial parameter vector to be optimized |
loglikelihood |
Function computing log-likelihood for current parameters |
gradient |
Function computing parameter gradients |
neghessian |
Function computing negative Hessian matrix |
tol |
Numeric convergence tolerance (default 1e-7) |
max_cnt |
Maximum number of optimization iterations (default 64) |
max_dmp_steps |
Maximum damping step attempts (default 16) |
Details
Implements a robust damped Newton-Raphson optimization algorithm.
Value
Optimized parameter estimates after convergence or reaching iteration limit
See Also
- nr_iterate
for parameter update computation
[Package lgspline version 0.2.0 Index]