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SLGP  

Spatial Logistic Gaussian Process for Field Density Estimation
View on CRAN: Click here


Download and install SLGP package within the R console
Install from CRAN:
install.packages("SLGP")

Install from Github:
library("remotes")
install_github("cran/SLGP")

Install by package version:
library("remotes")
install_version("SLGP", "1.0.1")



Attach the package and use:
library("SLGP")
Maintained by
Athénaïs Gautier
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-09-05
Latest Update: 2025-09-05
Description:
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>).
How to cite:
Athénaïs Gautier (2025). SLGP: Spatial Logistic Gaussian Process for Field Density Estimation. R package version 1.0.1, https://cran.r-project.org/web/packages/SLGP. Accessed 11 Sep. 2026.
Previous versions and publish date:
(2026-09-07 20:20), 1.0.0 (2025-09-05 22:50), 1.0.1 (2026-01-20 16:50), 1.0.2 (2026-02-17 22:00), 1.1.0 (2026-08-22 01:40)
Other packages that cited SLGP R package
View SLGP citation profile
Other R packages that SLGP depends, imports, suggests or enhances
Complete documentation for SLGP
Functions, R codes and Examples using the SLGP R package
Full SLGP package functions and examples
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