normalize_data

Scales the response and covariates of a dataset to the unit interval \([0,1]\).
This normalization is required before applying SLGP methods. If range bounds are
not provided, they are computed from the data.

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

normalize_data function

<dl><dt>data</dt>
<dd>A data frame containing the dataset.</dd>
<dt>predictorNames</dt>
<dd>A character vector of covariate column names.</dd>
<dt>responseName</dt>
<dd>A character string specifying the response variable name.</dd>
<dt>predictorsUpper</dt>
<dd>Optional numeric vector of upper bounds for covariates.</dd>
<dt>predictorsLower</dt>
<dd>Optional numeric vector of lower bounds for covariates.</dd>
<dt>responseRange</dt>
<dd>Optional numeric vector of length 2 giving lower and upper bounds for the response.</dd></dl>

Arguments

normalize_data: Normalize data to the range [0, 1] — normalize_data

<dl>

<dt>data</dt>
<dd>A data frame containing the dataset.</dd>


<dt>predictorNames</dt>
<dd>A character vector of covariate column names.</dd>


<dt>responseName</dt>
<dd>A character string specifying the response variable name.</dd>


<dt>predictorsUpper</dt>
<dd>Optional numeric vector of upper bounds for covariates.</dd>


<dt>predictorsLower</dt>
<dd>Optional numeric vector of lower bounds for covariates.</dd>


<dt>responseRange</dt>
<dd>Optional numeric vector of length 2 giving lower and upper bounds for the response.</dd>

</dl>

normalize_data: normalize_data: Normalize data to the range [0, 1]

Description

Usage

Value

Arguments