pre_comput_WNN

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

internal

Provides tools for conditional and spatially dependent
density estimation using Spatial Logistic Gaussian Processes (SLGPs).
The approach represents probability densities through finite-rank
Gaussian process priors transformed via a spatial logistic density
transformation, enabling flexible non-parametric modeling of
heterogeneous data. Functionality includes density prediction,
quantile and moment estimation, sampling methods, and preprocessing
routines for basis functions. Applications arise in spatial statistics,
machine learning, and uncertainty quantification.
The methodology builds on the framework of Leonard (1978)
<doi:10.1111/j.2517-6161.1978.tb01655.x>, Lenk (1988) <doi:10.1080/01621459.1988.10478625>,
Tokdar (2007) <doi:10.1198/106186007X210206>, Tokdar (2010) <doi:10.1214/10-BA605>,
and is further aligned with recent developments
in Bayesian non-parametric modelling: see Gautier (2023) <https://boristheses.unibe.ch/4377/>,
and Gautier (2025) <doi:10.48550/arXiv.2110.02876>).

Athénaïs Gautier

SLGP

Spatial Logistic Gaussian Process for Field Density Estimation

pre_comput_WNN function

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

Arguments

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

<dl>

<dt>normalizedData</dt>
<dd>Normalized data frame (\([0,1]\)-scaled).</dd>


<dt>predictorNames</dt>
<dd>Character vector of covariate names.</dd>


<dt>responseName</dt>
<dd>Name of the response variable.</dd>


<dt>nIntegral</dt>
<dd>Number of quadrature points for response domain.</dd>


<dt>nDiscret</dt>
<dd>Number of discretization steps for covariates.</dd>

</dl>

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

Description

Usage

Value

Arguments