Bayesian modelling of ARFIMA processes by Markov chain Monte Carlo methods

被引：0

作者：

Pai, JS ^{[1
]}

Ravishanker, N ^{[1
]}

机构：

[1] UNIV CONNECTICUT,DEPT STAT,STORRS,CT 06269

来源：

JOURNAL OF FORECASTING | 1996年 / 15卷 / 02期

关键词：

ARFIMA models; exact likelihood; model selection; partial linear regression coefficients;

D O I：

10.1002/(SICI)1099-131X(199603)15:2<63::AID-FOR606>3.0.CO;2-5

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This article describes Bayesian inference for autoregressive fractionally integrated moving average (ARFIMA) models using Markov chain Monte Carlo methods. The posterior distribution of the model parameters, corresponding to the exact likelihood function is obtained through the partial linear regression coefficients of the ARFIMA process. A Metropolis-Rao-Blackwellizallization approach is used for implementing sampling-based Bayesian inference. Bayesian model selection is discussed and implemented.

引用

页码：63 / 82

页数：20

共 50 条

[1] Bayesian estimation of filtered point processes using Markov chain Monte Carlo methods
Andrieu, C
Doucet, A
Duvaut, P
THIRTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2, 1998, : 1097 - 1101
[2] Introduction: Bayesian models and Markov chain Monte Carlo methods
Thomas, DC
GENETIC EPIDEMIOLOGY, 2001, 21 : S660 - S661
[3] Bayesian Mixture Modelling in Geochronology via Markov Chain Monte Carlo
Ajay Jasra
David A. Stephens
Kerry Gallagher
Christopher C. Holmes
Mathematical Geology, 2006, 38 : 269 - 300
[4] Bayesian mixture modelling in geochronology via Markov chain Monte Carlo
Jasra, Ajay
Stephens, David A.
Gallagher, Kerry
Holmes, Christopher C.
MATHEMATICAL GEOLOGY, 2006, 38 (03): : 269 - 300
[5] Bayesian phylogenetic inference via Markov chain Monte Carlo methods
Mau, B
Newton, MA
Larget, B
BIOMETRICS, 1999, 55 (01) : 1 - 12
[6] A comparison of Bayesian Markov chain Monte Carlo methods in a multilevel scenario
Karunarasan, Darshika
Sooriyarachchi, Roshini
Pinto, Vimukthini
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2023, 52 (10) : 4756 - 4772
[7] Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy
Sharma, Sanjib
ANNUAL REVIEW OF ASTRONOMY AND ASTROPHYSICS, VOL 55, 2017, 55 : 213 - 259
[8] Modelling maximum river flow by using Bayesian Markov Chain Monte Carlo
Cheong, R. Y.
Gabda, D.
1ST INTERNATIONAL CONFERENCE ON APPLIED & INDUSTRIAL MATHEMATICS AND STATISTICS 2017 (ICOAIMS 2017), 2017, 890
[9] Markov chain Monte Carlo methods for Bayesian gravitational radiation data analysis
Christensen, N
Meyer, R
PHYSICAL REVIEW D, 1998, 58 (08)
[10] Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models
Graham, Matthew M.
Thiery, Alexandre H.
Beskos, Alexandros
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2022, 84 (04) : 1229 - 1256

← 1 2 3 4 5 →