全球变化知识资源中心

Knowledge Resources Center for Global Change


Email:
Passwd
验证:
	换一张
Have you forgotten your password? Stay signed in Log In

globalchange > 过去全球变化的重建

DOI:	10.1371/journal.pone.0173453
论文题名:	Applying diffusion-based Markov chain Monte Carlo
作者:	Radu Herbei; Rajib Paul; L. Mark Berliner
刊名:	PLOS ONE
ISSN:	1932-6203
出版年:	2017
发表日期:	2017-3-16
卷:	12, 期:3
语种:	英语
英文关键词:	Markov models ; Algorithms ; Normal distribution ; Bayesian method ; Monte Carlo method ; Sea ice ; Velocity ; Differential equations
英文摘要:	We examine the performance of a strategy for Markov chain Monte Carlo (MCMC) developed by simulating a discrete approximation to a stochastic differential equation (SDE). We refer to the approach as diffusion MCMC. A variety of motivations for the approach are reviewed in the context of Bayesian analysis. In particular, implementation of diffusion MCMC is very simple to set-up, even in the presence of nonlinear models and non-conjugate priors. Also, it requires comparatively little problem-specific tuning. We implement the algorithm and assess its performance for both a test case and a glaciological application. Our results demonstrate that in some settings, diffusion MCMC is a faster alternative to a general Metropolis-Hastings algorithm.
URL:	http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0173453&type=printable
Citation statistics:
资源类型:	期刊论文
标识符:	http://119.78.100.158/handle/2HF3EXSE/25798
Appears in Collections:	过去全球变化的重建影响、适应和脆弱性科学计划与规划气候变化与战略全球变化的国际研究计划气候减缓与适应气候变化事实与影响

Files in This Item:	Download All

File Name/ File Size	Content Type	Version	Access	License
journal.pone.0173453.pdf（3206KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	View Download

作者单位:

The Ohio State University, Department of Statistics, Columbus, OH, United States of America;Western Michigan University, Department of Statistics, Kalamazoo, MI, United States of America;The Ohio State University, Department of Statistics, Columbus, OH, United States of America

Recommended Citation:

Radu Herbei,Rajib Paul,L. Mark Berliner. Applying diffusion-based Markov chain Monte Carlo[J]. PLOS ONE,2017-01-01,12(3)

Service
	Recommend this item
	Sava as my favorate item
	Show this item's statistics
	Export Endnote File
Google Scholar
	Similar articles in Google Scholar
	[Radu Herbei]'s Articles
	[Rajib Paul]'s Articles
	[L. Mark Berliner]'s Articles
百度学术
	Similar articles in Baidu Scholar
	[Radu Herbei]'s Articles
	[Rajib Paul]'s Articles
	[L. Mark Berliner]'s Articles
CSDL cross search
	Similar articles in CSDL Cross Search
	[Radu Herbei]‘s Articles
	[Rajib Paul]‘s Articles
	[L. Mark Berliner]‘s Articles
Related Copyright Policies
Null
收藏/分享