compute_Lambda {lgspline} | R Documentation |
Construct Smoothing Spline Penalty Matrix
Description
Builds penalty matrix combining smoothing spline and ridge penalties with optional predictor/partition-specific components. Handles custom penalties and scaling.
Usage
compute_Lambda(
custom_penalty_mat,
L1,
wiggle_penalty,
flat_ridge_penalty,
K,
nc,
unique_penalty_per_predictor,
unique_penalty_per_partition,
penalty_vec,
colnm_expansions,
just_Lambda = TRUE
)
Arguments
custom_penalty_mat |
Matrix; optional custom ridge penalty structure |
L1 |
Matrix; integrated squared second derivative penalty ( |
wiggle_penalty , flat_ridge_penalty |
Numeric; smoothing and ridge penalty parameters |
K |
Integer; number of interior knots ( |
nc |
Integer; number of basis columns per partition |
unique_penalty_per_predictor , unique_penalty_per_partition |
Logical; enable predictor/partition-specific penalties |
penalty_vec |
Named numeric; custom penalty values for predictors/partitions |
colnm_expansions |
Character; column names for linking penalties to predictors |
just_Lambda |
Logical; return only combined penalty matrix ( |
Value
List containing:
Lambda - Combined
nc \times nc
penalty matrix (\boldsymbol{\Lambda}
)L1 - Smoothing spline penalty matrix (
\textbf{L}_1
)L2 - Ridge penalty matrix (
\textbf{L}_2
)L_predictor_list - List of predictor-specific penalty matrices (
\textbf{L}_\text{predictor\_list}
)L_partition_list - List of partition-specific penalty matrices (
\textbf{L}_\text{partition\_list}
)
If just_Lambda=TRUE
and no partition penalties, returns only Lambda matrix \boldsymbol{\Lambda}
.