Cunningham, N;
Griffin, J;
Wild, D;
Lee, A;
(2019)
particleMDI: a Julia Package for the Integrative Cluster Analysis of Multiple Datasets.
In:
Proceedings of International Conference on Bayesian Statistics in Action BAYSM 2018: Bayesian Statistics and New Generations.
(pp. pp. 65-74).
Springer, Cham
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Abstract
We present particleMDI, a Julia package for performing integrative cluster analysis on multiple heterogeneous data sets, built within the framework of multiple data integration (MDI). particleMDI updates cluster allocations using a particle Gibbs approach which offers better mixing of the MCMC chain—but at greater computational cost—than the original MDI algorithm. We outline approaches for improving computational performance, finding the potential for greater than an order-of-magnitude improvement. We demonstrate the capability of particleMDI to uncovering the ground truth in simulated and real datasets. All files are available at https://github.com/nathancunn/particleMDI.jl
| Type: | Proceedings paper |
|---|---|
| Title: | particleMDI: a Julia Package for the Integrative Cluster Analysis of Multiple Datasets |
| Event: | International Conference on Bayesian Statistics in Action BAYSM 2018: Bayesian Statistics and New Generations |
| Location: | University of Warwick, Coventry, UK |
| Dates: | 02 July 2018 - 03 July 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-30611-3_7 |
| Publisher version: | https://doi.org/10.1007/978-3-030-30611-3_7 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Bayesian inference, Cluster analysis, Computational statistics, Data integration, Particle Monte Carlo methods |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10067900 |
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