{
  "abstract": "We propose a kernel-based estimation framework for Multivariate Generalized Gamma convolutions (MGGC), a class of probability distributions on R d + . MGGC are useful for risk modeling e.g. Their densities are in general not explicit. The construction relies on a new Stein operator for the MGGC class, derived from a partial differential equation satisfied by the characteristic function and expressed as an integral against the underlying Thorin measure. This leads to construct a new kernel and an estimation procedure in the derived reproducing kernel Hilbert space (RKHS); with consistency results. Numerical experiments illustrate the practical behaviour of the proposed estimator.",
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  "arxiv": "2609.24681",
  "author_total": 3,
  "authors": [
    {
      "name": "Léo Gonin"
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    {
      "name": "Esterina Masiello"
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    {
      "name": "Véronique Maume-Deschamps"
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  "bibtex": "https://research.draconitic.com/paper/e33526twdxara.bib",
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  "doi": "10.48550/arxiv.2609.24681",
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  "pdf_url": "https://hal.science/hal-05702801/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-07-23",
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  "ris": "https://research.draconitic.com/paper/e33526twdxara.ris",
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      "first_seen": "2026-10-30T12:17:21Z",
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      "url": "https://arxiv.org/abs/2609.24681"
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    {
      "field": "mathematics",
      "origin": "arxiv:math.PR",
      "subfield": "probability"
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    {
      "field": "mathematics",
      "origin": "arxiv:math.ST",
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  "title": "A Kernel Approach to Multivariate Generalized Gammas Convolutions",
  "title_text": "A Kernel Approach to Multivariate Generalized Gammas Convolutions",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:33Z",
  "url": "https://research.draconitic.com/paper/e33526twdxara",
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