Zero or One, Up or Down: Statistical Inference for Binary Data with Applications in Sensitivity Analysis of Energetic Materials
Doctoral thesis
Year
2024Metadata
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- Matematisk institutt [3780]
Abstract
This thesis is about statistical analysis of binary data, and presents both new methodological advances and practical applications. On the methodological side, the thesis presents a new importance sampling algorithm for estimating the marginal likelihood when using Bayesian nonparametric models for binary trials. This method relies on counting the symmetries arising from binary responses, thus turning a statistical problem into a combinatorial one. There are also theoretical developments regarding the large-sample theory of adaptive designs in binary regression, which are commonly employed in medicine, toxicology and industry. Regarding applications, the thesis focuses on enhancing statistical estimates of the sensitivity of explosives, with a particular emphasis on explosive remnants of war and dumped ammunition. It demonstrates that remnants of the high explosive amatol (widely used in both World Wars) are more sensitive to impact than previously assumed. Furthermore, the thesis presents recommendations for updating NATO's protocol for sensitivity measurements, so that researchers can extract more information from their experimental data.List of papers
Paper I. Christensen, D. Inference for Bayesian nonparametric models with binary response data via permutation counting. Bayesian Analysis 19, 293–318, 2024. DOI: 10.1214/22-BA1353. The article is included in the thesis. Also available at: https://doi.org/10.1214/22-BA1353 |
Paper II. Christensen, D.; Moen, P. A. J. perms: Likelihood-free estimation of marginal likelihoods for binary response data in Python and R. Submitted for publication, 2024. To be published. The paper is not available in DUO awaiting publishing. Preprint available in arXiv: arXiv:2309.01536 |
Paper III. Jensen, T. L.; Moxnes, J. F.; Unneberg, E.; Christensen, D. Models for predicting impact sensitivity of energetic materials based on the trigger linkage hypothesis and Arrhenius kinetics. Journal of Molecular Modeling 26, 2020. DOI: 10.1007/s00894-019-4269-z. The article is included in the thesis. Also available at: https://doi.org/10.1007/s00894-019-4269-z |
Paper IV. Christensen, D.; Unneberg, E.; Høyheim, E.; Jensen, T. L.; Hjort, N. L. Improved measurements of impact sensitivities of energetic materials. In Proceedings of the 25th International Seminar on New Trends in Research of Energetic Materials (NTREM), Institute of Energetic Materials, University of Pardubice, Czechia, 2023. The article is included in the thesis. |
Paper V. Christensen, D.; Stoltenberg, E. A.; Hjort, N. L. Sequential experimental designs in regression: Theory for the Bruceton and Langlie designs. Submitted for publication, 2023. To be published. The paper is not available in DUO awaiting publishing. Preprint available in arXiv: arXiv:2312.13387 |
Paper VI. Christensen, D.; Novik, G. P.; Unneberg, E. Estimating sensitivity with the Bruceton method: Setting the record straight. Submitted for publication, 2024. (Skal publiseres i??: Propellants, explosives, pyrotechnics). To be published. The paper is not available in DUO awaiting publishing. |
Paper VII. Novik, G. P.; Christensen, D. Increased impact sensitivity in ageing high explosives; analysis of Amatol extracted from explosive remnants of war. Royal Society Open Science. 2024, 11 (3), DOI: 10.1098/rsos.231344. The article is included in the thesis. Also available at: https://doi.org/10.1098/rsos.231344 |
Paper VIII. Nygård, S. T.; Christensen, D. Unlevel playing field: Evidence of ethnic discrimination in the access to children’s football from a field experiment in Norway. Submitted for publication, 2023. To be published. The paper is not available in DUO awaiting publishing. |