compute_dG_dlambda: Compute Derivative of Inverse-Information Matrix G with...

In lgspline: Lagrangian Multiplier Smoothing Splines for Smooth Function Estimation

Compute Derivative of Inverse-Information Matrix G with Respect to Lambda

Description

Calculates the derivative of the inverse-information matrix \textbf{G} with respect to the smoothing parameter \lambda, supporting both shared and partition-specific penalties.

Usage

compute_dG_dlambda(
  G,
  dPenalty_dlambda,
  K,
  unique_penalty_per_partition,
  dPenalty_partition_list,
  parallel,
  cl,
  chunk_size,
  num_chunks,
  rem_chunks
)

Arguments

G	A list of inverse-information matrices \textbf{G} for each partition
dPenalty_dlambda	Derivative of the shared penalty matrix with respect to \lambda.
K	Number of partitions minus 1 (K)
unique_penalty_per_partition	Logical indicating partition-specific penalties
dPenalty_partition_list	Optional list of derivatives of the partition-specific penalty matrices with respect to \lambda.
parallel	Logical to enable parallel processing
cl	Cluster object for parallel computation
chunk_size	Size of chunks for parallel processing
num_chunks	Number of chunks
rem_chunks	Remainder chunks

Value

A list of derivative matrices d\textbf{G}/d\lambda for each partition

lgspline documentation built on May 8, 2026, 5:07 p.m.