Outputs (9)

Nonparametric Predictive Inference for Discrete Lifetime Data (2024)
Journal Article
Coolen, F. P. A., Coolen-Maturi, T., & Mahnashi, A. M. Y. (2024). Nonparametric Predictive Inference for Discrete Lifetime Data. Mathematics, 12(22), Article 3514. https://doi.org/10.3390/math12223514

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. (2024). Reproducibility of estimates based on randomised response methods. Journal of statistical theory and practice, 18, Article 57. https://doi.org/10.1007/s42519-024-00409-z

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. (2024). 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 a... 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.