Markov chain Monte Carlo analysis of correlated count data

被引：161

作者：

Chib, S ^{[1
]}

Winkelmann, R

机构：

[1] Washington Univ, John M Olin Sch Business, St Louis, MO 63130 USA

[2] IZA Bonn, D-53072 Bonn, Germany

来源：

JOURNAL OF BUSINESS & ECONOMIC STATISTICS | 2001年 / 19卷 / 04期

关键词：

latent effects; Metropolis-Hastings algorithm; multivariate count data; Poisson-lognormal distribution;

D O I：

10.1198/07350010152596673

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This article is concerned with the analysis of correlated count data. A class of models is proposed in which the correlation among the counts is represented by correlated latent effects. Special cases of the model are discussed and a tuned and efficient Markov chain Monte Carlo algorithm is developed to estimate the model under both multivariate normal and multivariate-t assumptions on the latent effects. The methods are illustrated with two real data examples of six and sixteen variate correlated counts.

引用

页码：428 / 435

页数：8

共 50 条

[11] Markov chain Monte Carlo methods for Bayesian gravitational radiation data analysis
Christensen, N
Meyer, R
PHYSICAL REVIEW D, 1998, 58 (08)
[12] Markov chain Monte Carlo in the analysis of single-molecule experimental data
Kou, SC
Xie, XS
Liu, JS
MONTE CARLO METHOD IN THE PHYSICAL SCIENCES, 2003, 690 : 123 - 133
[13] Improving Markov Chain Monte Carlo algorithms in LISA Pathfinder Data Analysis
Karnesis, N.
Nofrarias, M.
Sopuerta, C. F.
Lobo, A.
9TH EDOARDO AMALDI CONFERENCE ON GRAVITATIONAL WAVES (AMALDI 9) AND THE 2011 NUMERICAL RELATIVITY - DATA ANALYSIS MEETING (NRDA 2011), 2012, 363
[14] Multivariate output analysis for Markov chain Monte Carlo
Vats, Dootika
Flegal, James M.
Jones, Galin L.
BIOMETRIKA, 2019, 106 (02) : 321 - 337
[15] Efficient Markov chain Monte Carlo with incomplete multinomial data
Ahn, Kwang Woo
Chan, Kung-Sik
STATISTICS AND COMPUTING, 2010, 20 (04) : 447 - 456
[16] Hierarchical models, data augmentation, and Markov chain Monte Carlo
van Dyk, DA
STATISTICAL CHALLENGES IN ASTRONOMY, 2003, : 41 - 56
[17] Image segmentation by Data Driven Markov Chain Monte Carlo
Tu, ZW
Zhu, SC
Shum, HY
EIGHTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOL II, PROCEEDINGS, 2001, : 131 - 138
[18] Efficient Markov chain Monte Carlo with incomplete multinomial data
Kwang Woo Ahn
Kung-Sik Chan
Statistics and Computing, 2010, 20 : 447 - 456
[19] Markov Chain Monte Carlo for generating ranked textual data
Cerqueti, Roy
Ficcadenti, Valerio
Dhesi, Gurjeet
Ausloos, Marcel
INFORMATION SCIENCES, 2022, 610 : 425 - 439
[20] Markov chain Monte Carlo data association for target tracking
Bergman, N
Doucet, A
2000 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS, VOLS I-VI, 2000, : 705 - 708

← 1 2 3 4 5 →