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Nonparametric Predictive Inference for Discrete Lifetime Data (2024)
Journal Article
Coolen, F. P. A., Coolen-Maturi, T., & Mahnashi, A. M. Y. (in press). Nonparametric Predictive Inference for Discrete Lifetime Data. Mathematics,

This paper presents nonparametric predictive inference for discrete lifetime data. While lifetimes are mostly treated as continuous random variables in statistics, there are scenarios where time observations are recorded as discrete values, for examp... Read More about Nonparametric Predictive Inference for Discrete Lifetime Data.

Reproducibility of estimates based on randomised response methods (2024)
Journal Article
Alghamdi, F. M., Coolen, F. P. A., & Coolen-Maturi, T. (in press). Reproducibility of estimates based on randomised response methods. Journal of statistical theory and practice,

A key aspect of statistical inference is estimation of population characteristic. This paper investigates the reproducibility of estimates of population characteristics. It focuses on estimates based on data collected by survey-based randomised respo... Read More about Reproducibility of estimates based on randomised response methods.

A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions (2024)
Journal Article
Einbeck, J., Coolen-Maturi, T., Uwimpuhwe, G., & Singh, A. (online). A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions. The Journal of Experimental Education, https://doi.org/10.1080/00220973.2024.2405738

The effectiveness of educational interventions has traditionally been evaluated using effect size measures which focus on a single feature of the distribution of the outcomes under intervention and control conditions: a (standardized) mean difference... Read More about A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions.

A Bayesian Imprecise Classification method that weights instances using the error costs (2024)
Journal Article
Moral-García, S., Coolen-Maturi, T., Coolen, F. P., & Abellán, J. (in press). A Bayesian Imprecise Classification method that weights instances using the error costs. Applied Soft Computing, 165, 112080. https://doi.org/10.1016/j.asoc.2024.112080


In practical applications, Bayesian classification methods have been successfully employed. The Naïve Bayes algorithm (NB) is a quick, successful, and well-known Bayesian classification method. The Naïve Credal Classifier (NCC) is... Read More about A Bayesian Imprecise Classification method that weights instances using the error costs.

Elicitation of Priors for Intervention Effects in Educational Trial Data (2024)
Book Chapter
Zhang, Q., Uwimpuhwe, G., Vallis, D., Singh, A., Coolen-Maturi, T., & Einbeck, J. (2024). Elicitation of Priors for Intervention Effects in Educational Trial Data. In J. Einbeck, H. Maeng, E. Ogundimu, & K. Perrakis (Eds.), Developments in Statistical Modelling (28-33). Springer. https://doi.org/10.1007/978-3-031-65723-8_5

Effect sizes for educational interventions are commonly small, and hence decisions to re-grant efficacy trials (small trials with homogeneous populations under idealized conditions) as effectiveness trials (larger trials with heterogeneous population... Read More about Elicitation of Priors for Intervention Effects in Educational Trial Data.

Survival Signature for Reliability Quantification of Large Systems and Networks (2024)
Presentation / Conference Contribution
Coolen, F. P. A., & Coolen-Maturi, T. (2024, July). Survival Signature for Reliability Quantification of Large Systems and Networks. Presented at The Nineteenth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, Brunów, Poland

The survival signature is a useful tool for quantification of reliability of large systems and networks with relatively few types of components. This paper provides an introductory overview of the survival signature, with emphasis on recent developme... Read More about Survival Signature for Reliability Quantification of Large Systems and Networks.

Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data (2024)
Journal Article
Coolen-Maturi, T., Mahnashi, A. M., & Coolen, F. P. A. (in press). Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data. Mathematical Methods of Statistics,

In reliability and survival analyses, right-censored observations are common. This type of data occurs when an event of interest is not fully observed during an experiment and there is no information provided about a random quantity, except that it e... Read More about Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data.

Smoothed Bootstrap Methods for Hypothesis Testing (2024)
Journal Article
Al Luhayb, A. S. M., Coolen-Maturi, T., & Coolen, F. P. A. (2024). Smoothed Bootstrap Methods for Hypothesis Testing. Journal of statistical theory and practice, 18(1), Article 16. https://doi.org/10.1007/s42519-024-00370-x

This paper demonstrates the application of smoothed bootstrap methods and Efron’s methods for hypothesis testing on real-valued data, right-censored data and bivariate data. The tests include quartile hypothesis tests, two sample medians and Pearson... Read More about Smoothed Bootstrap Methods for Hypothesis Testing.

Reproducibility of Statistical Tests Based on Randomised Response Data (2024)
Journal Article
Alghamdi, F. M., Coolen, F. P. A., & Coolen-Maturi, T. (2024). Reproducibility of Statistical Tests Based on Randomised Response Data. Journal of statistical theory and practice, 18(1), Article 13. https://doi.org/10.1007/s42519-024-00366-7

Reproducibility of experimental conclusions is an important topic in various fields, including social studies. The lack of reproducibility in research results not only limits scientific progress, but also wastes time, resources, and undermines societ... Read More about Reproducibility of Statistical Tests Based on Randomised Response Data.

Improving power calculations in educational trials (2023)
Report
Singh, A., Uwimpuhwe, G., Vallis, D., Akhter, N., Coolen-Maturi, T., Einbeck, J., Higgins, S., Culliney, M., & Demack, S. (2023). Improving power calculations in educational trials. Education Endowment Foundation

The aim of this study was to investigate and empirically derive parameters commonly used for statistical power and sample size calculations to better inform future trial design. Towards achieving this aim, the research project leveraged the richness... Read More about Improving power calculations in educational trials.

Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group (2023)
Presentation / Conference Contribution
Uwimpuhwe, G., Singh, A., Akhter, N., Ashraf, B., Coolen-Maturi, T., Robinson, T., Higgins, S., & Einbeck, J. (2023, July). Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group. Presented at International Workshop on Statistical Modelling, Dortmund

The Education Endowment Foundation (EEF), a charity aiming to break the link between socioeconomic disadvantage and pupil attainment, has commissioned over 200 randomised controlled trials. The collection of data from these trials, the `EEF Data Arch... Read More about Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group.

Smoothed bootstrap methods for bivariate data (2023)
Journal Article
Al Luhayb, A., Coolen-Maturi, T., & Coolen, F. (2023). Smoothed bootstrap methods for bivariate data. Journal of statistical theory and practice, 17(3), Article 37. https://doi.org/10.1007/s42519-023-00334-7

A smoothed bootstrap method is introduced for right-censored data based on the rightcensoring-A(n) assumption introduced by Coolen and Yan (2004), which is a generalization of Hill’s A(n) assumption (Hill, 1968) for right-censored data. The smoothed... Read More about Smoothed bootstrap methods for bivariate data.

A generalized system reliability model based on survival signature and multiple competing failure processes (2023)
Journal Article
Chang, M., Coolen, F., Coolen-Maturi, T., & Huang, X. (online). A generalized system reliability model based on survival signature and multiple competing failure processes. Journal of Computational and Applied Mathematics, 435, Article 115364. https://doi.org/10.1016/j.cam.2023.115364

Degradation-based system reliability analysis has been extensively conducted, but the components in a system are assumed to experience similar degradation and shock processes, neglecting actual failure mechanisms. However, multiple types of component... Read More about A generalized system reliability model based on survival signature and multiple competing failure processes.

New reliability model for complex systems based on stochastic processes and survival signature (2023)
Journal Article
Chang, M., Huang, X., Coolen, F., & Coolen-Maturi, T. (2023). New reliability model for complex systems based on stochastic processes and survival signature. European Journal of Operational Research, 309(3), 1349-1364. https://doi.org/10.1016/j.ejor.2023.02.027

For systems with complicated structures, reliability analysis based on survival signature has been carried out by modelling time-to-failure data with specific distributions. However, for highly reliable systems, only little or no failure data may be... Read More about New reliability model for complex systems based on stochastic processes and survival signature.

Smoothed Bootstrap for Right-Censored Data (2023)
Journal Article
Luhayb, A. S. M. A., Coolen, F. P., & Coolen-Maturi, T. (2023). Smoothed Bootstrap for Right-Censored Data. Communications in Statistics - Theory and Methods, https://doi.org/10.1080/03610926.2023.2171708

A smoothed bootstrap method is introduced for right-censored data based on the right-censoring-A(n) assumption introduced by Coolen and Yan, which is a generalization of Hill’s A(n) assumption for right-censored data. The smoothed bootstrap method is... Read More about Smoothed Bootstrap for Right-Censored Data.

Discussion of signature‐based models of preventive maintenance (2022)
Journal Article
Coolen, F. P., Coolen‐Maturi, T., & van Houtum, G. (2023). Discussion of signature‐based models of preventive maintenance. Applied Stochastic Models in Business and Industry, 39(1), 68-70. https://doi.org/10.1002/asmb.2716

As a contribution to the discussion of the paper An overview of some classical models and discussion of the signature-based models of preventive maintenance,1 we consider the assumption of exchangeability of the failure times of components in systems... Read More about Discussion of signature‐based models of preventive maintenance.

A Cost-Sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference (2022)
Journal Article
Moral-Garcia, S., Abellan, J., Coolen-Maturi, T., & Coolen, F. (2022). A Cost-Sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference. Applied Soft Computing, 123, Article 108916. https://doi.org/10.1016/j.asoc.2022.108916

Classifiers sometimes return a set of values of the class variable since there is not enough information to point to a single class value. These classifiers are known as imprecise classifiers. Decision Trees for Imprecise Classification were proposed... Read More about A Cost-Sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference.

Pricing exotic options in the incomplete market: an imprecise probability method (2022)
Journal Article
He, T., Coolen, F., & Coolen-Maturi, T. (2022). Pricing exotic options in the incomplete market: an imprecise probability method. Applied Stochastic Models in Business and Industry, 38(3), 422-440. https://doi.org/10.1002/asmb.2668

This paper considers a novel exotic option pricing method for incomplete markets. Nonparametric Predictive Inference (NPI) is applied to the option pricing procedure based on the binomial tree model allowing the method to evaluate exotic options with... Read More about Pricing exotic options in the incomplete market: an imprecise probability method.

Statistical reproducibility for pairwise t-tests in pharmaceutical research (2021)
Journal Article
Simkus, A., Coolen, F., Coolen-Maturi, T., Karp, N., & Bendtsen, C. (2022). Statistical reproducibility for pairwise t-tests in pharmaceutical research. Statistical Methods in Medical Research, 31(4), 673-688. https://doi.org/10.1177/09622802211041765

This paper investigates statistical reproducibility of the t-test. We formulate reproducibility as a predictive inference problem and apply the nonparametric predictive inference (NPI) method. Within our research framework, statistical reproducibilit... Read More about Statistical reproducibility for pairwise t-tests in pharmaceutical research.

Reliability analysis for systems based on degradation rates and hard failure thresholds changing with degradation levels (2021)
Journal Article
Chang, M., Huang, X., Coolen, F., & Coolen-Maturi, T. (2021). Reliability analysis for systems based on degradation rates and hard failure thresholds changing with degradation levels. Reliability Engineering & System Safety, 216, Article 108007. https://doi.org/10.1016/j.ress.2021.108007

Degradation-shock failure processes widely exist in practice, and extensive work has been carried out to better describe such processes. In this paper, a new model is developed for reliability analysis of systems subject to dependent degradation-shoc... Read More about Reliability analysis for systems based on degradation rates and hard failure thresholds changing with degradation levels.