{"id":800,"date":"2021-12-21T16:02:27","date_gmt":"2021-12-21T16:02:27","guid":{"rendered":"https:\/\/www.lancaster.ac.uk\/stor-i-student-sites\/thomas-newman\/?page_id=800"},"modified":"2021-12-29T13:59:15","modified_gmt":"2021-12-29T13:59:15","slug":"mres-and-msci","status":"publish","type":"page","link":"https:\/\/www.lancaster.ac.uk\/stor-i-student-sites\/thomas-newman\/research-2\/mres-and-msci\/","title":{"rendered":"MRes and MSci"},"content":{"rendered":"\t\t
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Bayesian Changepoint Detection<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tMSci dissertation, performing Bayesian analysis of a coal mining disasters data set.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tEmploying inference approaches (such as Gibbs sampling, Metropolis-Hastings algorithm, sequential importance sampling) to calculate the posteriors of changepoint locations and corresponding disaster rates using a semi-conjugate prior.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tSampling from the posterior predictive distribution to see how well the model explains my observations and implement marginal likelihood evaluation procedures to decide on the number of changepoints most suitable to explain data.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    Machine Learning in Simulations<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tConducted independent research as an intern at Âé¶¹¹ÙÍø on the STOR-i summer internship.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
    • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tFocused on machine learning in simulations, more specifically, simulation analytics. Researching how and why the performance of a system varies through time.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
    • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tPredicted whether simulated projects would finish early or late using multiple K-fold cross validation logistic regression on chronologically segmented systems.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
    • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tAnalysed the classification\u2019s output in order to understand how the importance of each variables in predicting the outcome of the project changes throughout time.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

      \/*! elementor – v3.5.3 – 28-12-2021 *\/ .elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px} Bayesian Changepoint Detection \/*! elementor – v3.5.3 – 28-12-2021 *\/ .elementor-widget.elementor-icon-list–layout-inline .elementor-widget-container{overflow:hidden}.elementor-widget .elementor-icon-list-items.elementor-inline-items{margin-right:-8px;margin-left:-8px}.elementor-widget 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