pre_comput_WNN: pre_comput_WNN: Precompute quantities for SLGP basis...

In SLGP: Spatial Logistic Gaussian Process for Field Density Estimation

pre_comput_WNN: Precompute quantities for SLGP basis evaluation with weighted nearest-neighbors

Description

Computes intermediate quantities for evaluating basis functions via weighted nearest-neighbor (WNN) interpolation on a discretized grid.

Usage

pre_comput_WNN(
  normalizedData,
  predictorNames,
  responseName,
  nIntegral = 101,
  nDiscret = 51
)

Arguments

normalizedData	Normalized data frame ([0,1]-scaled).
predictorNames	Character vector of covariate names.
responseName	Name of the response variable.
nIntegral	Number of quadrature points for response domain.
nDiscret	Number of discretization steps for covariates.

Value

A list of intermediate quantities:

• nodes: all evaluation points in response × covariates grid,

• indNodesToIntegral: indices to map nodes to response bins,

• indSamplesToNodes: index mapping from samples to grid nodes,

• weightSamplesToNodes: interpolation weights using inverse distance.

SLGP documentation built on Sept. 9, 2025, 5:25 p.m.