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National Institute for Applied Statistics Research Australia Seminar Series

March 28 @ 2:30 pm - 3:30 pm

Speaker:
Dr Matt Moore (UOW)

Title:
R package ‘bayesImageS’: a case study in Bayesian computation using Rcpp and OpenMP

Abstract:​
There are many approaches to Bayesian computation with intractable likelihoods, including the exchange algorithm, approximate Bayesian computation (ABC), thermodynamic integration, and composite likelihood. These approaches vary in accuracy as well as scalability for datasets of significant size. The Potts model is an example where such methods are required, due to its intractable normalising constant. This model is a type of Markov random field, which is commonly used for image segmentation. The dimension of its parameter space increases linearly with the number of pixels in the image, making this a challenging application for scalable Bayesian computation. My talk will introduce various algorithms in the context of the Potts model and describe their implementation in C++, using OpenMP for parallelism. I will also discuss the process of releasing this software as an open source R package on the CRAN repository.

Details

Date:
March 28
Time:
2:30 pm - 3:30 pm
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Organiser

NIASRA
Phone:
Pavel Krivitsky
Website:
https://niasra.uow.edu.au/index.html

Venue

Building 39A Room 208
University of Wollongong
Wollongong, NSW Australia
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