Noryanti, Muhammad and Coolen, Frank P. A. and Coolen-Maturi, Tahani (2017) Nonparametric predictive inference for combining diagnostic tests with parametric copula. In: 1st International Conference on Applied & Industrial Mathematics and Statistics 2017 (ICoAIMS 2017) , 8–10 August 2017 , Vistana City Centre, Kuantan, Pahang. pp. 1-6., 890 (1). ISSN 17426588
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Abstract
Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Statistical mechanics; Uncertainty analysis; Distribution functions |
| Subjects: | Q Science > QA Mathematics |
| Faculty/Division: | Faculty of Industrial Sciences And Technology |
| Depositing User: | Dr Noryanti Muhammad |
| Date Deposited: | 10 Jul 2018 02:27 |
| Last Modified: | 10 Jul 2018 02:27 |
| URI: | http://umpir.ump.edu.my/id/eprint/20615 |
| Download Statistic: | View Download Statistics |
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