Detecting Spatial Clusters via a Mixture of Dirichlet Processes
Joint Authors
Ray, Meredith A.
Zhang, Hongmei
Kang, Jian
Source
Journal of Probability and Statistics
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-18
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
We proposed an approach that has the ability to detect spatial clusters with skewed or irregular distributions.
A mixture of Dirichlet processes (DP) was used to describe spatial distribution patterns.
The effects of different batches of data collection efforts were also modeled with a Dirichlet process.
To cluster spatial foci, a birth-death process was applied due to its advantage of easier jumping between different numbers of clusters.
Inferences of parameters including clustering were drawn under a Bayesian framework.
Simulations were used to demonstrate and assess the method.
We applied the method to an fMRI meta-analysis dataset to identify clusters of foci corresponding to different emotions.
American Psychological Association (APA)
Ray, Meredith A.& Kang, Jian& Zhang, Hongmei. 2018. Detecting Spatial Clusters via a Mixture of Dirichlet Processes. Journal of Probability and Statistics،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1197681
Modern Language Association (MLA)
Ray, Meredith A.…[et al.]. Detecting Spatial Clusters via a Mixture of Dirichlet Processes. Journal of Probability and Statistics No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1197681
American Medical Association (AMA)
Ray, Meredith A.& Kang, Jian& Zhang, Hongmei. Detecting Spatial Clusters via a Mixture of Dirichlet Processes. Journal of Probability and Statistics. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1197681
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197681