Computational challenges and temporal dependence in Bayesian nonparametric models

被引：0

作者：

Argiento, Raffaele ^{[1
,2
]}

Ruggiero, Matteo ^{[1
,2
]}

机构：

[1] Univ Torino, Turin, Italy

[2] Coll Carlo Alberto, Turin, Italy

来源：

STATISTICAL METHODS AND APPLICATIONS | 2018年 / 27卷 / 02期

关键词：

Bayesian dependent model; Conjugacy; Computation; Dirichlet; Transition function; FLEMING-VIOT PROCESS; DENSITY-ESTIMATION; SAMPLING METHODS; DIRICHLET; MIXTURE; INFERENCE; DISTRIBUTIONS;

D O I：

10.1007/s10260-017-0397-8

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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

引用

页码：231 / 238

页数：8

共 50 条

[1] Computational challenges and temporal dependence in Bayesian nonparametric models
Raffaele Argiento
Matteo Ruggiero
[J]. Statistical Methods & Applications, 2018, 27 : 231 - 238
[2] A tutorial on Bayesian nonparametric models
Gershman, Samuel J.
Blei, David M.
[J]. JOURNAL OF MATHEMATICAL PSYCHOLOGY, 2012, 56 (01) : 1 - 12
[3] An adaptive truncation method for inference in Bayesian nonparametric models
Griffin, J. E.
[J]. STATISTICS AND COMPUTING, 2016, 26 (1-2) : 423 - 441
[4] Sequentially allocated merge-split samplers for conjugate Bayesian nonparametric models
Dahl, David B.
Newcomb, Spencer
[J]. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2022, 92 (07) : 1487 - 1511
[5] Full uncertainty analysis for Bayesian nonparametric mixture models
Moya, Blake
Walker, Stephen G.
[J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2024, 189
[6] Geometric Sensitivity Measures for Bayesian Nonparametric Density Estimation Models
Saha, Abhijoy
Kurtek, Sebastian
[J]. SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY, 2019, 81 (01): : 104 - 143
[7] IS INFINITY THAT FAR? A BAYESIAN NONPARAMETRIC PERSPECTIVE OF FINITE MIXTURE MODELS
Argiento, Raffaele
De Iorio, Maria
[J]. ANNALS OF STATISTICS, 2022, 50 (05) : 2641 - 2663
[8] Bayesian Nonparametric Modeling of Conditional Multidimensional Dependence Structures
Barone, Rosario
Dalla Valle, Luciana
[J]. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2023, 32 (04) : 1361 - 1370
[9] Fundamentals of Nonparametric Bayesian Line Detection
van Rossum, Anne C.
Lin, Hai Xiang
Dubbeldam, Johan
van den Herik, H. Jaap
[J]. PATTERN RECOGNITION APPLICATIONS AND METHODS, ICPRAM 2016, 2017, 10163 : 175 - 193
[10] Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination
Yau, Christopher
Holmes, Chris
[J]. BAYESIAN ANALYSIS, 2011, 6 (02): : 329 - 351

← 1 2 3 4 5 →