{
  "abstract": "The SLGP package provides nonparametric estimation of fields of probability densities indexed by covariates, from unevenly sized samples with few or no replicates. A Spatial Logistic Gaussian Process applies a logistic density transformation to a finite-rank Gaussian process over a joint index-response domain, yielding a prior over conditional densities that adapts in location, shape, and modality. The contribution of this paper is the implementation: a finite-rank Random-Fourier-Feature representation that keeps the transformed process numerically tame, a log-concave likelihood that makes the fit a convex problem, and a family of quadrature shortcuts for the normalising integrals that turn a per-observation cost into a per-grid cost. Three estimation modes are available: MAP, Laplace, and full MCMC. We demonstrate the package throughout on the classical Fiji-Tonga earthquake catalogue, estimating how the distribution of hypocentre depths deforms across the region, and on a discrete-response variant.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.33827",
  "author_total": 1,
  "authors": [
    {
      "name": "Athénaïs Gautier"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2r5mdznatns9p.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.33827",
  "fulltext_url": null,
  "id": "2r5mdznatns9p",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.33827",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.AP"
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    [
      "arxiv",
      "stat.ME"
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    [
      "openalex",
      "1702|Gaussian Processes and Bayesian Inference"
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  "openalex": "W7214743311",
  "pdf_url": "https://arxiv.org/pdf/2609.33827",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2r5mdznatns9p.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:26Z",
      "native_id": "2609.33827",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.33827"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "SLGP: An R Package for Spatial Conditional Density Estimation",
  "title_text": "SLGP: An R Package for Spatial Conditional Density Estimation",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:26Z",
  "url": "https://research.draconitic.com/paper/2r5mdznatns9p",
  "venue": "arXiv",
  "versions": []
}