Staff profile

• Decision Theory
• Imprecise Probability
• Nonparametric Predictive Inference
• Operations Research
• Reliability Theory
• Statistics

• 2000: Editorial activities: Member of editorial boards of the following journals: Journal of Risk and Reliability; Quality and Reliability Engineering International; Journal of Statistical Theory and Practice; Communications in Statistics - Theory and Methods; Communications in Statistics - Simulation and Computation; Communications in Statistics - Case Studies, Data Analysis and Applications; Life Cycle Reliability and Safety Engineering; European Journal of Technology and Design; Journal of the Polish Safety and Reliability Association; TransNav.

Chapter in book

• Survival Signatures for System Reliability
  Coolen, F. P., & Coolen‐Maturi, T. (2022). Survival Signatures for System Reliability. In Wiley StatsRef: Statistics Reference Online. Wiley. https://doi.org/10.1002/9781118445112.stat08331
• The survival signature for quantifying system reliability: an introductory overview from practical perspective
  Coolen, F., & Coolen-Maturi, T. (2021). The survival signature for quantifying system reliability: an introductory overview from practical perspective. In C. van Gulijk, & E. Zaitseva (Eds.), Reliability Engineering and Computational Intelligence (23-37). Springer Verlag. https://doi.org/10.1007/978-3-030-74556-1_2
• Bayesian graphical models for high complexity testing: aspects of implementation
  Wooff, D., Goldstein, M., & Coolen, F. (2018). Bayesian graphical models for high complexity testing: aspects of implementation. In R. Kenett, F. Ruggeri, & F. Faltin (Eds.), Analytic methods in systems and software testing (213-243). Wiley. https://doi.org/10.1002/9781119357056.ch8
• Nonparametric Predictive Precedence Testing for Two Groups.
  Coolen-Schrijner, P., Maturi, T., & Coolen, F. P. A. (2009). Nonparametric Predictive Precedence Testing for Two Groups. In Imprecision in Statistical Theory and Practice (91-105). Grace Scientific Publishing LLC

Conference Paper

• Survival Signature for Reliability Quantification of Large Systems and Networks
  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
• Imprecise system reliability using the survival signature
  Coolen, F., Coolen-Maturi, T., Aslett, L., & Walter, G. (2016, May). Imprecise system reliability using the survival signature. Presented at 1st International Conference on Applied Mathematics in Engineering and Reliability, Ho Chi Minh City, Vietnam
• Adaptive (opportunity-based) age replacement strategies
  Coolen, F., Coolen-Schrijner, P., & Shaw, S. (2004, December). Adaptive (opportunity-based) age replacement strategies. Presented at 5th IMA International Conference on Modelling in Industrial Maintenance and Reliability, Salford

Edited book

• Uncertainty in Engineering - Introduction to Methods and Applications
  Aslett, L., Coolen, F., & De Bock, J. (Eds.). (2022). Uncertainty in Engineering - Introduction to Methods and Applications. Springer Verlag. https://doi.org/10.1007/978-3-030-83640-5

Journal Article

• A generalized system reliability model based on survival signature and multiple competing failure processes
  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
• Statistical Perspectives on Reproducibility: Definitions and Challenges
  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
• Parametric Predictive Bootstrap Method for the Reproducibility of Hypothesis Tests
  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
• Exceedance probabilities using Nonparametric Predictive Inference
  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
• Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data
  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
• Nonparametric Predictive Inference for Discrete Lifetime Data
  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
• A Bayesian Imprecise Classification method that weights instances using the error costs
  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
• Reproducibility of estimates based on randomised response methods
  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
• Reproducibility of mean estimators under ranked set sampling
  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
• Reproducibility of Statistical Tests Based on Randomised Response Data
  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
• Smoothed Bootstrap Methods for Hypothesis Testing
  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
• Smoothed Bootstrap for Right-Censored Data
  Luhayb, A. S. M. A., Coolen, F. P., & Coolen-Maturi, T. (2024). Smoothed Bootstrap for Right-Censored Data. Communications in Statistics - Theory and Methods, 53(11), 4037-4061. https://doi.org/10.1080/03610926.2023.2171708
• New reliability model for complex systems based on stochastic processes and survival signature
  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
• Smoothed bootstrap methods for bivariate data
  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
• Logic Differential Calculus for Reliability Analysis Based on Survival Signature
  Rusnak, P., Zaitseva, E., Coolen, F., Kvassay, M., & Levashenko, V. (2023). Logic Differential Calculus for Reliability Analysis Based on Survival Signature. IEEE Transactions on Dependable and Secure Computing, 20(2), 1529-1540. https://doi.org/10.1109/tdsc.2022.3159126
• Discussion of signature‐based models of preventive maintenance
  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
• Discussion of specifying prior distributions in reliability applications
  Coolen, F. (2023). Discussion of specifying prior distributions in reliability applications. Applied Stochastic Models in Business and Industry, 40(1), 108-110. https://doi.org/10.1002/asmb.2799
• A monotonicity property of weighted log-rank tests
  Coolen-Maturi, T., & Coolen, F. (2023). A monotonicity property of weighted log-rank tests. Communications in Statistics - Theory and Methods, 52(7), 2402-2416. https://doi.org/10.1080/03610926.2021.1952270
• A Cost-Sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference
  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
• Pricing exotic options in the incomplete market: an imprecise probability method
  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
• Statistical reproducibility for pairwise t-tests in pharmaceutical research
  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
• Survival signature for reliability evaluation of a multi-state system with multi-state components
  Qin, J., & Coolen, F. (2022). Survival signature for reliability evaluation of a multi-state system with multi-state components. Reliability Engineering & System Safety, 218(Part A), Article 108129. https://doi.org/10.1016/j.ress.2021.108129
• Counterfactual explanation of machine learning survival models
  Kovalev, M., Utkin, L., Coolen, F., & Konstantinov, A. (2022). Counterfactual explanation of machine learning survival models. Informatica: An International Journal, 32(4), 817-847. https://doi.org/10.15388/21-infor468
• Reliability analysis for systems based on degradation rates and hard failure thresholds changing with degradation levels
  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
• Imprecise inference based on the log-rank test for accelerated life testing
  Coolen, F., Ahmadini, A., & Coolen-Maturi, T. (2021). Imprecise inference based on the log-rank test for accelerated life testing. Metrika, 84, 913-925. https://doi.org/10.1007/s00184-021-00807-4
• The joint survival signature of coherent systems with shared components
  Coolen-Maturi, T., Coolen, F. P., & Balakrishnan, N. (2021). The joint survival signature of coherent systems with shared components. Reliability Engineering & System Safety, 207, Article 107350. https://doi.org/10.1016/j.ress.2020.107350
• Nonparametric predictive inference for comparison of two diagnostic tests
  Alabdulhadi, M., Coolen-Maturi, T., & Coolen, F. (2021). Nonparametric predictive inference for comparison of two diagnostic tests. Communications in Statistics - Theory and Methods, 50(19), 4470-4486. https://doi.org/10.1080/03610926.2020.1719157
• Nonparametric Predictive Inference for American Option Pricing based on the Binomial Tree Model
  He, T., Coolen, F., & Coolen-Maturi, T. (2021). Nonparametric Predictive Inference for American Option Pricing based on the Binomial Tree Model. Communications in Statistics - Theory and Methods, 50(20), 4657-4684. https://doi.org/10.1080/03610926.2020.1764040
• A new boosting-based software reliability growth model
  Utkin, L., & Coolen, F. (2021). A new boosting-based software reliability growth model. Communications in Statistics - Theory and Methods, 50(24), 6167-6194. https://doi.org/10.1080/03610926.2020.1740736
• A practical reliability design method considering the compound weight and load-sharing
  Li, Y., Coolen, F., & Zhu, C. (2020). A practical reliability design method considering the compound weight and load-sharing. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 127, 17-32. https://doi.org/10.1016/j.ijar.2020.09.001
• Nonparametric predictive inference for test reproducibility by sampling future data orderings
  Coolen, F., & Marques, F. (2020). Nonparametric predictive inference for test reproducibility by sampling future data orderings. Journal of statistical theory and practice, 14(4), Article 62. https://doi.org/10.1007/s42519-020-00127-2
• Non-linear failure rate: A Bayes study using Hamiltonian Monte Carlo simulation
  Thach, T., Bris, R., Volf, P., & Coolen, F. (2020). Non-linear failure rate: A Bayes study using Hamiltonian Monte Carlo simulation. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 123, 55-76. https://doi.org/10.1016/j.ijar.2020.04.007
• Imprecise weighted extensions of random forests for classification and regression
  Utkin, L., Kovalev, M., & Coolen, F. (2020). Imprecise weighted extensions of random forests for classification and regression. Applied Soft Computing, 92, Article 106324. https://doi.org/10.1016/j.asoc.2020.106324
• Reliability analysis of phased mission systems when components can be swapped upon failure
  Coolen, F., Huang, X., & Najem, A. (2020). Reliability analysis of phased mission systems when components can be swapped upon failure. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2), Article 020905. https://doi.org/10.1115/1.4046328
• Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test
  Coolen, F., & Bin Himd, S. (2020). Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test. Journal of statistical theory and practice, 14(2), Article 26. https://doi.org/10.1007/s42519-020-00097-5
• Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature
  Li, Y., Coolen, F., Zhu, C., & Tan, J. (2020). Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature. Renewable Energy, 153, 766-776. https://doi.org/10.1016/j.renene.2020.02.017
• A new study on reliability importance analysis of phased mission systems
  Huang, X., Coolen, F., Coolen-Maturi, T., & Zhang, Y. (2020). A new study on reliability importance analysis of phased mission systems. IEEE Transactions on Reliability, 69(2), 522-532. https://doi.org/10.1109/tr.2019.2923695
• Statistical inference for the Arrhenius-Weibull accelerated life testing model with imprecision based on the likelihood ratio test
  Ahmadini, A., & Coolen, F. (2020). Statistical inference for the Arrhenius-Weibull accelerated life testing model with imprecision based on the likelihood ratio test. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 234(2), 275-289. https://doi.org/10.1177/1748006x19884860
• Estimation of small area total with randomized data
  Ahmed, S., Shabbir, J., Gupta, S., & Coolen, F. (2020). Estimation of small area total with randomized data. Revstat Statistical Journal, 18(2), 223-235
• Nonparametric predictive inference for diagnostic test thresholds
  Coolen-Maturi, T., Coolen, F., & Alabdulhadi, M. (2020). Nonparametric predictive inference for diagnostic test thresholds. Communications in Statistics - Theory and Methods, 49(3), 697-725. https://doi.org/10.1080/03610926.2018.1549249
• Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains
  Li, Y., & Coolen, F. (2019). Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(6), 1074-1085. https://doi.org/10.1177/1748006x19859690
• Non‐parametric predictive inference for the validation of credit rating systems
  Coolen-Maturi, T., & Coolen, F. (2019). Non‐parametric predictive inference for the validation of credit rating systems. Journal of the Royal Statistical Society: Series A, 182(4), 1189-1204. https://doi.org/10.1111/rssa.12416
• Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals
  Alabdulhadi, M., Coolen, F., & Coolen-Maturi, T. (2019). Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals. Journal of statistical theory and practice, 13, Article 38. https://doi.org/10.1007/s42519-019-0039-6
• Reliability analysis of general phased mission systems with a new survival signature
  Huang, X., Aslett, L. J., & Coolen, F. P. (2019). Reliability analysis of general phased mission systems with a new survival signature. Reliability Engineering & System Safety, 189, 416-422. https://doi.org/10.1016/j.ress.2019.04.019
• Extending the survival signature paradigm to complex systems with non-repairable dependent failures
  George-Williams, H., Feng, G., Coolen, F., Beer, M., & Patelli, E. (2019). Extending the survival signature paradigm to complex systems with non-repairable dependent failures. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(4), 505-519. https://doi.org/10.1177/1748006x18808085
• Nonparametric Predictive Inference for European Option Pricing based on the Binomial Tree Model
  He, T., Coolen, F., & Coolen-Maturi, T. (2019). Nonparametric Predictive Inference for European Option Pricing based on the Binomial Tree Model. Journal of the Operational Research Society, 70(10), 1692-1708. https://doi.org/10.1080/01605682.2018.1495997
• A heuristic survival signature based approach for reliability-redundancy allocation
  Huang, X., Coolen, F., & Coolen-Maturi, T. (2019). A heuristic survival signature based approach for reliability-redundancy allocation. Reliability Engineering & System Safety, 185, 511-517. https://doi.org/10.1016/j.ress.2019.02.010
• Robustness of nonparametric predictive inference for future order statistics
  Alqifari, H., & Coolen, F. (2019). Robustness of nonparametric predictive inference for future order statistics. Journal of statistical theory and practice, 13(1), Article 12. https://doi.org/10.1007/s42519-018-0011-x
• Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests
  Marques, F., Coolen, F., & Coolen-Maturi, T. (2019). Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests. Journal of statistical theory and practice, 13, Article 15. https://doi.org/10.1007/s42519-018-0020-9
• Approximations for the likelihood ratio statistic for hypothesis testing between two Beta distributions
  Marques, F., Coolen, F., & Coolen-Maturi, T. (2019). Approximations for the likelihood ratio statistic for hypothesis testing between two Beta distributions. Journal of statistical theory and practice, 13, Article 17. https://doi.org/10.1007/s42519-018-0021-8
• On nonparametric predictive inference for asset and European option trading in the binomial tree model
  Chen, J., Coolen, F., & Coolen-Maturi, T. (2019). On nonparametric predictive inference for asset and European option trading in the binomial tree model. Journal of the Operational Research Society, 70(10), 1678-1691. https://doi.org/10.1080/01605682.2019.1643682
• Applying prospect theory to multi-attribute problems with independence assumptions
  Stanley, J., & Coolen, F. (2019). Applying prospect theory to multi-attribute problems with independence assumptions. Involve, 12(4), 687-711. https://doi.org/10.2140/involve.2019.12.687
• Reliability sensitivity analysis of coherent systems based on survival signature
  Huang, X., & Coolen, F. (2018). Reliability sensitivity analysis of coherent systems based on survival signature. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 232(6), 627-634. https://doi.org/10.1177/1748006x18754974
• System reliability and component importance when components can be swapped upon failure
  Najem, A., & Coolen, F. (2018). System reliability and component importance when components can be swapped upon failure. Applied Stochastic Models in Business and Industry, 35(3), 399-413. https://doi.org/10.1002/asmb.2420
• Imprecise probabilistic inference for software run reliability growth models
  Utkin, L., & Coolen, F. (2018). Imprecise probabilistic inference for software run reliability growth models. Journal of uncertain systems, 12(4), 292-308
• Nonparametric predictive inference with parametric copulas for combining bivariate diagnostic tests
  Muhammad, N., Coolen-Maturi, T., & Coolen, F. (2018). Nonparametric predictive inference with parametric copulas for combining bivariate diagnostic tests. Statistics, optimization & information computing, 6(3), 398-408. https://doi.org/10.19139/soic.v6i3.579
• Robust Bayesian reliability for complex systems under prior-data conflict
  Walter, G., & Coolen, F. (2018). Robust Bayesian reliability for complex systems under prior-data conflict. Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 4(3), Article 04018025. https://doi.org/10.1061/ajrua6.0000974
• A robust weighted SVR-based software reliability growth model
  Utkin, L., & Coolen, F. (2018). A robust weighted SVR-based software reliability growth model. Reliability Engineering & System Safety, 176, 93-101. https://doi.org/10.1016/j.ress.2018.04.007
• k-Boxplots for mixture data
  Qarmalah, N. M., Einbeck, J., & Coolen, F. P. (2018). k-Boxplots for mixture data. Statistical Papers, 59(2), 513-528. https://doi.org/10.1007/s00362-016-0774-7
• Nonparametric predictive inference for future order statistics
  Coolen, F., Coolen-Maturi, T., & Alqifari, H. (2018). Nonparametric predictive inference for future order statistics. Communications in Statistics - Theory and Methods, 47(10), 2527-2548. https://doi.org/10.1080/03610926.2017.1342834
• Nonparametric predictive inference for reproducibility of two basic tests based on order statistics
  Coolen, F., & Alqifari, H. (2018). Nonparametric predictive inference for reproducibility of two basic tests based on order statistics. Revstat Statistical Journal, 16(2), 167-185
• Marginal and joint reliability importance based on survival signature
  Eryilmaz, S., Coolen, F., & Coolen-Maturi, T. (2018). Marginal and joint reliability importance based on survival signature. Reliability Engineering & System Safety, 172, 118-128. https://doi.org/10.1016/j.ress.2017.12.002
• Mean residual life of coherent systems consisting of multiple types of dependent components
  Eryilmaz, S., Coolen, F., & Coolen-Maturi, T. (2018). Mean residual life of coherent systems consisting of multiple types of dependent components. Naval Research Logistics, 65(1), 86-97. https://doi.org/10.1002/nav.21782
• An imprecise statistical method for accelerated life testing using the power-Weibull model
  Yin, Y.-C., Coolen, F., & Coolen-Maturi, T. (2017). An imprecise statistical method for accelerated life testing using the power-Weibull model. Reliability Engineering & System Safety, 167, 158-167. https://doi.org/10.1016/j.ress.2017.05.045
• Optimisation of maintenance policy under parameter uncertainty using portfolio theory
  Wu, S., Coolen, F., & Liu, B. (2017). Optimisation of maintenance policy under parameter uncertainty using portfolio theory. IISE Transactions, 49(7), 711-721. https://doi.org/10.1080/24725854.2016.1267881
• Nonparametric predictive inference for stock returns
  Baker, R., Coolen-Maturi, T., & Coolen, F. (2017). Nonparametric predictive inference for stock returns. Journal of Applied Statistics, 44(8), 1333-1349. https://doi.org/10.1080/02664763.2016.1204429
• Mixture Models for Prediction from Time Series, with Application to Energy Use Data
  Qarmalah, N. M., Einbeck, J., & Coolen, F. P. (2017). Mixture Models for Prediction from Time Series, with Application to Energy Use Data. Archives of data science. Series A, 2(1), 1-15. https://doi.org/10.5445/ksp/1000058749/07
• Simulation Methods for System Reliability Using the Survival Signature
  Patelli, E., Feng, G., Coolen, F., & Coolen-Maturi, T. (2017). Simulation Methods for System Reliability Using the Survival Signature. Reliability Engineering & System Safety, 167, 327-337. https://doi.org/10.1016/j.ress.2017.06.018
• Bayesian nonparametric system reliability using sets of priors
  Walter, G., Aslett, L., & Coolen, F. (2017). Bayesian nonparametric system reliability using sets of priors. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 80(1), 67-88. https://doi.org/10.1016/j.ijar.2016.08.005
• On the structure function and survival signature for system reliability
  Coolen, F., & Coolen-Maturi, T. (2016). On the structure function and survival signature for system reliability. Safety and Reliability, 36(2), 77-87. https://doi.org/10.1080/09617353.2016.1219936
• The structure function for system reliability as predictive (imprecise) probability
  Coolen, F., & Coolen-Maturi, T. (2016). The structure function for system reliability as predictive (imprecise) probability. Reliability Engineering & System Safety, 154, 180-187. https://doi.org/10.1016/j.ress.2016.06.008
• Predictive inference for bivariate data: Combining nonparametric predictive inference for marginals with an estimated copula
  Coolen-Maturi, T., Coolen, F., & Muhammad, N. (2016). Predictive inference for bivariate data: Combining nonparametric predictive inference for marginals with an estimated copula. Journal of statistical theory and practice, 10(3), 515-538. https://doi.org/10.1080/15598608.2016.1184112
• Imprecise system reliability and component importance based on survival signature
  Feng, G., Patelli, E., Beer, M., & Coolen, F. (2016). Imprecise system reliability and component importance based on survival signature. Reliability Engineering & System Safety, 150, 116-125. https://doi.org/10.1016/j.ress.2016.01.019
• Bayesian inference for reliability of systems and networks using the survival signature
  Aslett, L., Coolen, F., & Wilson, S. (2015). Bayesian inference for reliability of systems and networks using the survival signature. Risk Analysis, 35(9), 1640-1651. https://doi.org/10.1111/risa.12228
• A conjugate class of utility functions for sequential decision problems
  Houlding, B., Coolen, F., & Bolger, D. (2015). A conjugate class of utility functions for sequential decision problems. Risk Analysis, 35(9), 1611-1622. https://doi.org/10.1111/risa.12359
• Nonparametric Predictive Inference with Combined Data Under Different Right-Censoring Schemes
  Coolen-Maturi, T., & Coolen, F. (2015). Nonparametric Predictive Inference with Combined Data Under Different Right-Censoring Schemes. Journal of statistical theory and practice, 9(2), 288-304. https://doi.org/10.1080/15598608.2014.886313
• Imprecise inference for warranty contract analysis
  Utkin, L., Coolen, F., & Gurov, S. (2015). Imprecise inference for warranty contract analysis. Reliability Engineering & System Safety, 138, 31-39. https://doi.org/10.1016/j.ress.2015.01.011
• Predictive inference for system reliability after common-cause component failures
  Coolen, F., & Coolen-Maturi, T. (2015). Predictive inference for system reliability after common-cause component failures. Reliability Engineering & System Safety, 135, 27-33. https://doi.org/10.1016/j.ress.2014.11.005
• Interval estimation for proportional reversed hazard family based on lower record values
  Wang, B., Yu, K., & Coolen, F. (2015). Interval estimation for proportional reversed hazard family based on lower record values. Statistics and Probability Letters, 98, 115-122. https://doi.org/10.1016/j.spl.2014.12.019
• Imprecise individual risk models of insurance
  Utkin, L., & Coolen, F. (2015). Imprecise individual risk models of insurance. Journal of uncertain systems, 9(3), 198-214
• Nonparametric predictive inference for system reliability using the survival signature
  Coolen, F., Coolen-Maturi, T., & Al-nefaiee, A. (2014). Nonparametric predictive inference for system reliability using the survival signature. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 228(5), 437-448. https://doi.org/10.1177/1748006x14526390
• Three-group ROC analysis: a nonparametric predictive approach
  Coolen-Maturi, T., Elkhafifi, F., & Coolen, F. (2014). Three-group ROC analysis: a nonparametric predictive approach. Computational Statistics & Data Analysis, 78, 69-81. https://doi.org/10.1016/j.csda.2014.04.005
• Nonparametric predictive inference for combined competing risks data
  Coolen-Maturi, T., & Coolen, F. (2014). Nonparametric predictive inference for combined competing risks data. Reliability Engineering & System Safety, 126, 87-97. https://doi.org/10.1016/j.ress.2014.01.007
• Classification with support vector machines and Kolmogorov-Smirnov bounds
  Utkin, L., & Coolen, F. (2014). Classification with support vector machines and Kolmogorov-Smirnov bounds. Journal of statistical theory and practice, 8(2), 297-318. https://doi.org/10.1080/15598608.2013.788985
• Classification with decision trees from a nonparametric predictive inference perspective
  Abellán, J., Baker, R., Coolen, F., Crossman, R., & Masegosa, A. (2014). Classification with decision trees from a nonparametric predictive inference perspective. Computational Statistics & Data Analysis, 71, 789-802. https://doi.org/10.1016/j.csda.2013.02.009
• Nonparametric predictive inference for reliability of a k-out-of-m:G system with multiple component types
  Aboalkhair, A., Coolen, F., & MacPhee, I. (2014). Nonparametric predictive inference for reliability of a k-out-of-m:G system with multiple component types. Reliability Engineering & System Safety, 131, 298-304. https://doi.org/10.1016/j.ress.2014.04.010
• Nonparametric predictive inference for reproducibility of basic nonparametric tests
  Coolen, F., & Bin Himd, S. (2014). Nonparametric predictive inference for reproducibility of basic nonparametric tests. Journal of statistical theory and practice, 8(4), 591-618. https://doi.org/10.1080/15598608.2013.819792
• Nonparametric predictive inference for system failure time based on bounds for the signature
  Al-Nefaiee, A., & Coolen, F. (2013). Nonparametric predictive inference for system failure time based on bounds for the signature. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 227(5), 513-522. https://doi.org/10.1177/1748006x13485188
• Nonparametric predictive reliability of series of voting systems
  Aboalkhair, A., Coolen, F., & MacPhee, I. (2013). Nonparametric predictive reliability of series of voting systems. European Journal of Operational Research, 226(1), 77-84. https://doi.org/10.1016/j.ejor.2012.11.001
• Maximum group sizes for simultaneous testing in high potential risk scenarios
  Coolen, F. (2013). Maximum group sizes for simultaneous testing in high potential risk scenarios. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 227(6), 569-575. https://doi.org/10.1177/1748006x13489483
• A cost-based importance measure for system components: An extension of the Birnbaum importance
  Wu, S., & Coolen, F. (2013). A cost-based importance measure for system components: An extension of the Birnbaum importance. European Journal of Operational Research, 225(1), 189-195. https://doi.org/10.1016/j.ejor.2012.09.034
• Nonparametric predictive inference for binary diagnostic tests
  Coolen-Maturi, T., Coolen-Schrijner, P., & Coolen, F. (2012). Nonparametric predictive inference for binary diagnostic tests. Journal of statistical theory and practice, 6(4), 665-680. https://doi.org/10.1080/15598608.2012.719800
• Nonparametric predictive multiple comparisons of lifetime data
  Coolen-Maturi, T., Coolen-Schrijner, P., & Coolen, F. (2012). Nonparametric predictive multiple comparisons of lifetime data. Communications in Statistics - Theory and Methods, 41(22), 4164-4181. https://doi.org/10.1080/03610926.2011.569863
• Nonparametric predictive inference for failure times of systems with exchangeable components
  Coolen, F., & Al-nefaiee, A. (2012). Nonparametric predictive inference for failure times of systems with exchangeable components. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 226(3), 262-273. https://doi.org/10.1177/1748006x11418430
• Nonparametric predictive inference for diagnostic accuracy
  Coolen-Maturi, T., Coolen-Schrijner, P., & Coolen, F. (2012). Nonparametric predictive inference for diagnostic accuracy. Journal of Statistical Planning and Inference, 142(5), 1141-1150. https://doi.org/10.1016/j.jspi.2011.11.015
• A nonparametric predictive approach to sequential acceptance problems
  Elsaeiti, M., & Coolen, F. (2012). A nonparametric predictive approach to sequential acceptance problems. Journal of statistical theory and practice, 6(3), 383-401. https://doi.org/10.1080/15598608.2012.695930
• Nonparametric predictive inference for accuracy of ordinal diagnostic tests
  Elkhafifi, F., & Coolen, F. (2012). Nonparametric predictive inference for accuracy of ordinal diagnostic tests. Journal of statistical theory and practice, 6(4), 681-697. https://doi.org/10.1080/15598608.2012.719802
• Nonparametric predictive utility inference
  Houlding, B., & Coolen, F. (2012). Nonparametric predictive utility inference. European Journal of Operational Research, 221(1), 222-230. https://doi.org/10.1016/j.ejor.2012.03.024
• Unobserved, re-defined, unknown or removed failure modes in competing risks
  Coolen-Maturi, T., & Coolen, F. (2011). Unobserved, re-defined, unknown or removed failure modes in competing risks. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 225(4), 461-474. https://doi.org/10.1177/1748006x11401706
• The shape of the hazard rate for finite continuous-time birth–death processes
  Crossman, R., Coolen-Schrijner, P., & Coolen, F. (2011). The shape of the hazard rate for finite continuous-time birth–death processes. Statistics and Probability Letters, 81(2), 181-187. https://doi.org/10.1016/j.spl.2010.10.018
• Considerations on jury size and composition using lower probabilities
  Coolen, F., Houlding, B., & Parkinson, S. (2011). Considerations on jury size and composition using lower probabilities. Journal of Statistical Planning and Inference, 141(1), 382-391. https://doi.org/10.1016/j.jspi.2010.06.014
• Adaptive utility and trial aversion.
  Houlding, B., & Coolen, F. (2011). Adaptive utility and trial aversion. Journal of Statistical Planning and Inference, 141(2), 734-747. https://doi.org/10.1016/j.jspi.2010.07.023
• Maximising entropy on the nonparametric predictive inference model for multinomial data
  Abellán, J., Baker, R., & Coolen, F. (2011). Maximising entropy on the nonparametric predictive inference model for multinomial data. European Journal of Operational Research, 212(1), 112-122. https://doi.org/10.1016/j.ejor.2011.01.020
• Nonparametric predictive selection with early experiment termination.
  Coolen-Maturi, T., Coolen-Schrijner, P., & Coolen, F. (2011). Nonparametric predictive selection with early experiment termination. Journal of Statistical Planning and Inference, 141(4), 1403-1421. https://doi.org/10.1016/j.jspi.2010.10.018
• Imprecise probability in statistical inference and decision making
  Augustin, T., Coolen, F. P., Moral, S., & Troffaes, M. C. (2010). Imprecise probability in statistical inference and decision making. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 51(9), 1011-1013. https://doi.org/10.1016/j.ijar.2010.08.001
• Nonparametric predictive comparison of lifetime data under progressive censoring
  Maturi, T. A., Coolen-Schrijner, P., & Coolen, F. P. A. (2010). Nonparametric predictive comparison of lifetime data under progressive censoring. Journal of Statistical Planning and Inference, 140(2), 515-525. https://doi.org/10.1016/j.jspi.2009.07.027
• Nonparametric predictive inference for exposure assessment
  Roelofs, V., Coolen, F., & Hart, A. (2010). Nonparametric predictive inference for exposure assessment. Risk Analysis, 31(2), 218-227. https://doi.org/10.1111/j.1539-6924.2010.01490.x
• Nonparametric predictive category selection for multinomial data
  Baker, R., & Coolen, F. (2010). Nonparametric predictive category selection for multinomial data. Journal of statistical theory and practice, 4(3), 509-526. https://doi.org/10.1080/15598608.2010.10412000
• Extended opportunity-based age replacement with a one-cycle criterion
  Venkat, D., Coolen, F., & Coolen-Schrijner, P. (2010). Extended opportunity-based age replacement with a one-cycle criterion. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 224(1), 55-62. https://doi.org/10.1243/1748006xjrr275
• New interval Bayesian models for software reliability based on non-homogeneous Poisson processes
  Utkin, L., Zatenko, S., & Coolen, F. (2010). New interval Bayesian models for software reliability based on non-homogeneous Poisson processes. Automation and Remote Control, 71(5), 935-944. https://doi.org/10.1134/s0005117910050218
• On modelling of grouped reliability data for wind turbines
  Coolen, F., Spinato, F., & Venkat, D. (2010). On modelling of grouped reliability data for wind turbines. IMA Journal of Management Mathematics, 21(4), 363-372. https://doi.org/10.1093/imaman/dpn012
• Nonparametric predictive inference for competing risks.
  Maturi, T., Coolen-Schrijner, P., & Coolen, F. (2010). Nonparametric predictive inference for competing risks. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 224(1), 11-26. https://doi.org/10.1243/1748006xjrr263
• Imprecision in Statistical Theory and Practice
  Coolen-Schrijner, P., Coolen, F. P., Troffaes, M. C., & Augustin, T. (2009). Imprecision in Statistical Theory and Practice. Journal of statistical theory and practice, 3(1), 1-9
• Applying the imprecise Dirichlet model in cases with partial observations and dependencies in failure data
  Troffaes, M., & Coolen, F. (2009). Applying the imprecise Dirichlet model in cases with partial observations and dependencies in failure data. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 50(2), 257-268. https://doi.org/10.1016/j.ijar.2008.03.013
• Opportunity-based age replacement with a one-cycle criterion
  Coolen-Schrijner, P., Shaw, S., & Coolen, F. (2009). Opportunity-based age replacement with a one-cycle criterion. Journal of the Operational Research Society, 60(10), 1428-1438. https://doi.org/10.1057/jors.2008.99
• Nonparametric predictive precedence testing for two groups
  Coolen-Schrijner, P., Maturi, T., & Coolen, F. (2009). Nonparametric predictive precedence testing for two groups. Journal of statistical theory and practice, 3(1), 273-287. https://doi.org/10.1080/15598608.2009.10411925
• Nonparametric predictive methods for acceptance sampling
  Coolen, F., & Elsaeiti, M. (2009). Nonparametric predictive methods for acceptance sampling. Journal of statistical theory and practice, 3(4), 907-921. https://doi.org/10.1080/15598608.2009.10411969
• A nonparametric predictive alternative to the Imprecise Dirichlet Model: the case of a known number of categories.
  Coolen, F., & Augustin, T. (2009). A nonparametric predictive alternative to the Imprecise Dirichlet Model: the case of a known number of categories. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 50(2), 217-230. https://doi.org/10.1016/j.ijar.2008.03.011
• Time-homogeneous birth-death processes with probability intervals and absorbing state
  Crossman, R., Coolen-Schrijner, P., & Coolen, F. (2009). Time-homogeneous birth-death processes with probability intervals and absorbing state. Journal of statistical theory and practice, 3(1), 103-118. https://doi.org/10.1080/15598608.2009.10411914
• Nonparametric predictive pairwise comparison for real-valued data with terminated tails
  Maturi, T. A., Coolen-Schrijner, P., & Coolen, F. P. A. (2009). Nonparametric predictive pairwise comparison for real-valued data with terminated tails. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, 51(1), 141-150. https://doi.org/10.1016/j.ijar.2009.09.005
• Nonparametric predictive system reliability with redundancy allocation following component testing
  MacPhee, I., Coolen, F., & Aboalkhair, A. (2009). Nonparametric predictive system reliability with redundancy allocation following component testing. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 223(3), 181-188. https://doi.org/10.1243/1748006xjrr239
• Bayesian probability boxes in risk assessment
  Montgomery, V., Coolen, F., & Hart, A. (2009). Bayesian probability boxes in risk assessment. Journal of statistical theory and practice, 3(1), 69-83. https://doi.org/10.1080/15598608.2009.10411912
• Nonparametric predictive inference for system reliability with redundancy allocation.
  Coolen-Schrijner, P., Coolen, F., & MacPhee, I. (2008). Nonparametric predictive inference for system reliability with redundancy allocation. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 222(4), 463-476. https://doi.org/10.1243/1748006xjrr179
• Two nonparametric predictive control charts
  Arts, G., & Coolen, F. (2008). Two nonparametric predictive control charts. Journal of statistical theory and practice, 2(4), 499-512. https://doi.org/10.1080/15598608.2008.10411890
• Nonparametric predictive comparison of proportions
  Coolen, F., & Coolen-Schrijner, P. (2007). Nonparametric predictive comparison of proportions. Journal of Statistical Planning and Inference, 137(1), 23-33. https://doi.org/10.1016/j.jspi.2005.11.008
• Nonparametric prediction of unobserved failure modes
  Coolen, F. (2007). Nonparametric prediction of unobserved failure modes. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 221(3), 207-216. https://doi.org/10.1243/1748006xjrr61
• On nonparametric predictive inference and abjective Bayesianism
  Coolen, F. (2006). On nonparametric predictive inference and abjective Bayesianism. Journal of Logic, Language and Information, 15(1-2), 21-47. https://doi.org/10.1007/s10849-005-9005-7
• Nonparametric adaptive opportunity-based replacement strategies
  Coolen-Schrijner, P., Coolen, F., & Shaw, S. (2006). Nonparametric adaptive opportunity-based replacement strategies. Journal of the Operational Research Society, 57(1), 63-81. https://doi.org/10.1057/palgrave.jors.2601954
• Bayesian reliability demonstration with multiple independent tasks.
  Coolen, F., Coolen-Schrijner, P., & Rahrouh, M. (2005). Bayesian reliability demonstration with multiple independent tasks. IMA Journal of Management Mathematics, 17(2), 131-142. https://doi.org/10.1093/imaman/dpi030
• Bayesian reliability demonstration for failure-free periods
  Coolen, F., Coolen-Schrijner, P., & Rahrouh, R. (2005). Bayesian reliability demonstration for failure-free periods. Reliability Engineering & System Safety, 88(1), 81-91. https://doi.org/10.1016/j.ress.2004.07.015
• Nonparametric predictive reliability demonstration for failure-free periods
  Coolen, F., & Coolen-Schrijner, P. (2005). Nonparametric predictive reliability demonstration for failure-free periods. IMA Journal of Management Mathematics, 16(1), 1-11. https://doi.org/10.1093/imaman/dph025
• Nonparametric predictive inference with right-censored data
  Coolen, F., & Yan, K. (2004). Nonparametric predictive inference with right-censored data. Journal of Statistical Planning and Inference, 126(1), 25-54. https://doi.org/10.1016/j.jspi.2003.07.004
• Nonparametric predictive inference and interval probability
  Augustin, T., & Coolen, F. (2004). Nonparametric predictive inference and interval probability. Journal of Statistical Planning and Inference, 124(2), 251-272. https://doi.org/10.1016/j.jspi.2003.07.003
• A nonparametric predictive method for queues.
  Coolen, F., & Coolen-Schrijner, P. (2003). A nonparametric predictive method for queues. European Journal of Operational Research, 145(2), 425-442. https://doi.org/10.1016/s0377-2217%2802%2900179-0
• Nonparametric predictive inference in reliability.
  Coolen, F., Coolen-Schrijner, P., & Yan, K. (2002). Nonparametric predictive inference in reliability. Reliability Engineering & System Safety, 78(2), 185-193. https://doi.org/10.1016/s0951-8320%2802%2900162-x
• Bayesian Graphical Models for Software Testing
  Wooff, D., Goldstein, M., & Coolen, F. (2002). Bayesian Graphical Models for Software Testing. IEEE Transactions on Software Engineering, 28(5), 510-525. https://doi.org/10.1109/tse.2002.1000453
• Condition monitoring: a new perspective
  Coolen, F., & Coolen-Schrijner, P. (2000). Condition monitoring: a new perspective. Journal of the Operational Research Society, 51, 311-319
• Low structure imprecise predictive inference for Bayes' problem
  Coolen, F. (1998). Low structure imprecise predictive inference for Bayes' problem. Statistics and Probability Letters, 36, 349-357
• An imprecise Dirichlet model for Bayesian analysis of failure data including right-censored observations
  Coolen, F. (1997). An imprecise Dirichlet model for Bayesian analysis of failure data including right-censored observations