Stein operators, kernels and discrepancies for multivariate continuous distributions - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2019

Stein operators, kernels and discrepancies for multivariate continuous distributions

Résumé

We present a general framework for setting up Stein's method for multivariate continuous distributions. The approach gives a collection of Stein characterizations, among which we highlight score-Stein operators and kernel-Stein operators. Applications include copu-las and distance between posterior distributions. We give a general explicit construction for Stein kernels for elliptical distributions and discuss Stein kernels in generality, highlighting connections with Fisher information and mass transport. Finally, a goodness-of-fit test based on Stein discrepancies is given.
Fichier principal
Vignette du fichier
MRS1911-vf.pdf (602.73 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02420874 , version 1 (20-12-2019)

Identifiants

  • HAL Id : hal-02420874 , version 1

Citer

Guillaume Mijoule, Gesine Reinert, Yvik Swan. Stein operators, kernels and discrepancies for multivariate continuous distributions. 2019. ⟨hal-02420874⟩
62 Consultations
484 Téléchargements

Partager

Gmail Facebook X LinkedIn More