Computational challenges and temporal dependence in Bayesian nonparametric models

Raffaele Argiento; Matteo Ruggiero

doi:10.1007/s10260-017-0397-8

Computational challenges and temporal dependence in Bayesian nonparametric models

Raffaele Argiento
, Matteo Ruggiero^*

^*Autore corrispondente per questo lavoro

Facoltà di Economia

University of Turin

Risultato della ricerca: Contributo in rivista › Articolo › peer review

Abstract

Abstract Müller et al. (Stat Methods Appl, 2017) provide an excellent review of\r\nseveral classes of Bayesian nonparametric models which have found widespread application in a variety of contexts, successfully highlighting their flexibility in comparison\r\nwith parametric families. Particular attention in the paper is dedicated to modelling\r\nspatial dependence. Here we contribute by concisely discussing general computational\r\nchallenges which arise with posterior inference with Bayesian nonparametric models\r\nand certain aspects of modelling temporal dependence.

Lingua originale	Inglese
pagine (da-a)	231-238
Numero di pagine	8
Rivista	Statistical Methods and Applications
Volume	27
Numero di pubblicazione	2
DOI	https://doi.org/10.1007/s10260-017-0397-8
Stato di pubblicazione	Pubblicato - 2018

All Science Journal Classification (ASJC) codes

Statistica e Probabilità
Statistica, Probabilità e Incertezza

Keywords

Bayesian dependent model
Computation
Conjugacy
Dirichlet
Probability and Uncertainty
Statistics
Statistics and Probability
Transition function

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10.1007/s10260-017-0397-8

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author = "Raffaele Argiento and Matteo Ruggiero",

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doi = "10.1007/s10260-017-0397-8",

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AU - Ruggiero, Matteo

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AB - Abstract Müller et al. (Stat Methods Appl, 2017) provide an excellent review of\r\nseveral classes of Bayesian nonparametric models which have found widespread application in a variety of contexts, successfully highlighting their flexibility in comparison\r\nwith parametric families. Particular attention in the paper is dedicated to modelling\r\nspatial dependence. Here we contribute by concisely discussing general computational\r\nchallenges which arise with posterior inference with Bayesian nonparametric models\r\nand certain aspects of modelling temporal dependence.

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KW - Probability and Uncertainty

KW - Statistics

KW - Statistics and Probability

KW - Transition function

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KW - Computation

KW - Conjugacy

KW - Dirichlet

KW - Probability and Uncertainty

KW - Statistics

KW - Statistics and Probability

KW - Transition function

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Computational challenges and temporal dependence in Bayesian nonparametric models

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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