Outputs (147)

Statistical Perspectives on Reproducibility: Definitions and Challenges (2025)
Journal Article
Simkus, A., Coolen-Maturi, T., Coolen, F. P., & Bendtsen, C. (2025). Statistical Perspectives on Reproducibility: Definitions and Challenges. Journal of statistical theory and practice, 19(3), Article 40. https://doi.org/10.1007/s42519-025-00459-x

Reproducibility is a widely discussed topic, yet many experimental results cannot be confirmed due to factors such as publication bias, poor documentation, and inappropriate statistical methods. A lack of standard definitions for reproducibility and... Read More about Statistical Perspectives on Reproducibility: Definitions and Challenges.

Exceedance probabilities using Nonparametric Predictive Inference (2025)
Journal Article
Mahnashi, A. M., Coolen, F. P., & Coolen-Maturi, T. (2025). Exceedance probabilities using Nonparametric Predictive Inference. Franklin Open, 11, Article 100241. https://doi.org/10.1016/j.fraope.2025.100241

Some statistical methods for extreme value analysis assume that the maximum observed value represents the endpoint of the support. However, in cases involving right-censored observations, it is often unclear whether the true value o... Read More about Exceedance probabilities using Nonparametric Predictive Inference.

Parametric Predictive Bootstrap Method for the Reproducibility of Hypothesis Tests (2025)
Journal Article
Aldawsari, A. M. A., Coolen-Maturi, T., & Coolen, F. P. A. (2025). Parametric Predictive Bootstrap Method for the Reproducibility of Hypothesis Tests. Journal of statistical theory and practice, 19(2), Article 21. https://doi.org/10.1007/s42519-025-00438-2

Hypothesis tests are essential tools in applied statistics, but their results can vary when repeated. The reproducibility probability (RP) quantifies the probability of obtaining the same test outcome—either rejecting or not rejecting the null hypoth... Read More about Parametric Predictive Bootstrap Method for the Reproducibility of Hypothesis Tests.

Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data (2024)
Journal Article
Coolen-Maturi, T., Mahnashi, A. M., & Coolen, F. P. A. (2024). Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data. Mathematical Methods of Statistics, 33(4), 338-372. https://doi.org/10.3103/S1066530724700182

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.

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 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.

Reproducibility of mean estimators under ranked set sampling (2024)
Journal Article
Rehman, S. A., Coolen-Maturi, T., Coolen, F. P., & Shabbir, J. (2024). Reproducibility of mean estimators under ranked set sampling. Franklin Open, 8, Article 100139. https://doi.org/10.1016/j.fraope.2024.100139

In statistical inferences, the estimation of population parameters using information obtained from a sample is an important method. This involves choosing an appropriate sampling method to collect data. An efficient sampling method used for data coll... Read More about Reproducibility of mean estimators under ranked set sampling.

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.

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.