Print  Close

Bayesian Clustering for Distributions

Abstract Number:

3308 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Mihoko Minami (1), Cleridy Lennert-Cody (2)

Institutions:

(1) Keio University, Yokohama, Japan, (2) Inter-American Tropical Tuna Commission, La Jolla, California

Co-Author:

Cleridy Lennert-Cody  
Inter-American Tropical Tuna Commission

First Author:

Mihoko Minami  
Keio University

Presenting Author:

Mihoko Minami  
Keio University

Abstract Text:

Scientists often collect samples on characteristics of different observation units and wonder whether the characteristics of the observation units have similar distributional structure. In this study, we propose a new Bayesian clustering method for distributions that uses a T-EP (Truncated Ewens-Pitman) distribution as the prior for the partitioning parameters, that is, for the number of clusters and the cluster sizes. For a given number of clusters, we consider an entropy-based objective function that is naturally derived from the modified Jensen-Shannon divergence between two distributions. This leads to a hierarchical Bayesian clustering method for distributions.

As a motivational example, we introduce yellowfin tuna fork length data collected from the tuna catch of purse-seine vessels that operated in the eastern Pacific Ocean. The hierarchical Bayesian clustering method, applied to density estimates of yellowfin tuna fork length for 5-degree square areas, was used to explore spatial structure in the length composition of the tuna catch.

Keywords:

Hierarchical Bayesian model|Modified Jensen-Shannon divergence|Clustering for distributions|Truncated Ewens-Pitman distribution|Density estimates|

Sponsors:

Section on Statistics and the Environment

Tracks:

Spatio-temporal statistics

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

No

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand