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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.

Discussion of specifying prior distributions in reliability applications (2023)
Journal Article
Coolen, F. (2023). Discussion of specifying prior distributions in reliability applications. Applied Stochastic Models in Business and Industry, https://doi.org/10.1002/asmb.2799

The paper Specifying Prior Distributions in Reliability Applications (Tian et al. (2023)) mainly provides an overview of methods for selecting noninformative prior distributions for parameters of basic lifetime distributions, as often used in reliabi... Read More about Discussion of specifying prior distributions in reliability applications.

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. (2023). A generalized system reliability model based on survival signature and multiple competing failure processes. Journal of Computational and Applied Mathematics, 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.

Logic Differential Calculus for Reliability Analysis Based on Survival Signature (2022)
Journal Article
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

The structure function is an often-used mathematical representation of the investigated system in reliability analysis. It is a binary function that models system state according to states of its components. The size of the structure function depends... Read More about Logic Differential Calculus for Reliability Analysis Based on Survival Signature.

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.

Counterfactual explanation of machine learning survival models (2021)
Journal Article
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

A method for counterfactual explanation of machine learning survival models is proposed. One of the difficulties of solving the counterfactual explanation problem is that the classes of examples are implicitly defined through outcomes of a machine le... Read More about Counterfactual explanation of machine learning survival models.

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.

Survival signature for reliability evaluation of a multi-state system with multi-state components (2021)
Journal Article
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

Survival signature technology has recently attracted increasing attention for its merits on quantifying reliability of systems with multiple types of components. In order to implement reliability evaluation of multi-state system (MSS), computing meth... Read More about Survival signature for reliability evaluation of a multi-state system with multi-state components.

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.

A monotonicity property of weighted log-rank tests (2021)
Journal Article
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

The logrank test is a well-known nonparametric test which is often used to compare the survival distributions of two samples including right-censored observations, it is also known as the Mantel-Haenszel test. The Gρ family of tests, generalizes the... Read More about A monotonicity property of weighted log-rank tests.

Imprecise inference based on the log-rank test for accelerated life testing (2021)
Journal Article
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

This paper presents an imprecise predictive inference method for accelerated life testing. The method is largely nonparametric, with a basic parametric function to link different stress levels. The log-rank test is used to provide imprecision for the... Read More about Imprecise inference based on the log-rank test for accelerated life testing.

The joint survival signature of coherent systems with shared components (2020)
Journal Article
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

The concept of joint bivariate signature, introduced by Navarro et al. [13], is a useful tool for quantifying the reliability of two systems with shared components. As with the univariate system signature, introduced by Samaniego [17], its applicatio... Read More about The joint survival signature of coherent systems with shared components.

A practical reliability design method considering the compound weight and load-sharing (2020)
Journal Article
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

Reliability design is an important work in the early design stage of offshore wind turbines. Due to the incomplete considerations and poor feasibility of the drawbacks for existing methods, a set of the practical reliability design method is proposed... Read More about A practical reliability design method considering the compound weight and load-sharing.

Nonparametric predictive inference for test reproducibility by sampling future data orderings (2020)
Journal Article
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

This paper considers nonparametric predictive inference (NPI) for reproducibility of likelihood ratio tests with the test criterion in terms of the sample mean. Given a sample of size n used for the actual test, the NPI approach provides lower and up... Read More about Nonparametric predictive inference for test reproducibility by sampling future data orderings.

Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test (2020)
Journal Article
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

This paper introduces a new bootstrap method based on the nonparametric predictive inference (NPI) approach to statistics. NPI is a frequentist statistics framework which explicitly focuses on prediction of future observations. The NPI framework enab... Read More about Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test.

Non-linear failure rate: A Bayes study using Hamiltonian Monte Carlo simulation (2020)
Journal Article
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

A generalization of the linear failure rate called non-linear failure rate is introduced, analyzed, and applied to real data sets for both censored and uncensored data. The Hamiltonian Monte Carlo and cross-entropy methods have been exploited to empo... Read More about Non-linear failure rate: A Bayes study using Hamiltonian Monte Carlo simulation.

Nonparametric Predictive Inference for American Option Pricing based on the Binomial Tree Model (2020)
Journal Article
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

In this article, we present the American option pricing procedure based on the binomial tree from an imprecise statistical aspect. Nonparametric Predictive Inference (NPI) is implemented to infer imprecise probabilities of underlying asset movements,... Read More about Nonparametric Predictive Inference for American Option Pricing based on the Binomial Tree Model.

Estimation of small area total with randomized data (2020)
Journal Article
Ahmed, S., Shabbir, J., Gupta, S., & Coolen, F. (2020). Estimation of small area total with randomized data. Revstat Statistical Journal, 18(2), 223-235

In social surveys involving questions that are sensitive or personal in nature, respondents may not provide correct answers to certain questions asked by the interviewer. The impact of this nonresponse or inaccurate response becomes even more acute i... Read More about Estimation of small area total with randomized data.

Imprecise weighted extensions of random forests for classification and regression (2020)
Journal Article
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

One of the main problems of using the random forests (RF) in classification and regression tasks is a lack of sufficient data which fall into certain leaves of trees in order to estimate the tree predicted values. To cope with this problem, robust im... Read More about Imprecise weighted extensions of random forests for classification and regression.

Reliability analysis of phased mission systems when components can be swapped upon failure (2020)
Journal Article
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

This paper proposes a new strategy to improve the reliability of phased mission systems (PMS), namely, by swapping of components. In the proposed strategy, when a component fails, it can be swapped by another one in the system which is still function... Read More about Reliability analysis of phased mission systems when components can be swapped upon failure.

A new boosting-based software reliability growth model (2020)
Journal Article
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 new software reliability growth model (SRGM) called RBoostSRGM is proposed in this paper. It can be regarded as a modification of the boosting SRGMs through the use of a reduced set of weights to take into account the behavior of the software relia... Read More about A new boosting-based software reliability growth model.

Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature (2020)
Journal Article
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

The hydraulic system is one of the most critical subsystems of wind turbines. It is used to reset the aerodynamic brakes. Because of this, the reliability of the hydraulic system is important to the functioning of the entire wind turbine. To realisti... Read More about Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature.

Nonparametric predictive inference for comparison of two diagnostic tests (2020)
Journal Article
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

An important aim in diagnostic medical research is comparison of the accuracy of two diagnostic tests. In this paper, comparison of two diagnostic tests is presented using nonparametric predictive inference (NPI) for future order statistics. The test... Read More about Nonparametric predictive inference for comparison of two diagnostic tests.

Statistical inference for the Arrhenius-Weibull accelerated life testing model with imprecision based on the likelihood ratio test (2019)
Journal Article
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

In this paper, we present a new imprecise statistical inference method for accelerated life testing data, where nonparametric predictive inferences at normal stress levels are integrated with a parametric Arrhenius-Weibull model. The method includes... Read More about Statistical inference for the Arrhenius-Weibull accelerated life testing model with imprecision based on the likelihood ratio test.

On nonparametric predictive inference for asset and European option trading in the binomial tree model (2019)
Journal Article
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

This paper introduces a novel method for asset and option trading in a binomial scenario. This method uses nonparametric predictive inference (NPI), a statistical methodology within im- precise probability theory. Instead of inducing a single probabi... Read More about On nonparametric predictive inference for asset and European option trading in the binomial tree model.

A new study on reliability importance analysis of phased mission systems (2019)
Journal Article
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

Reliability importance which serves to quantify the influence of each component (or each type of components) in each phase on the reliability of a phased mission system (PMS) plays an important role in security assessment and risk management. In this... Read More about A new study on reliability importance analysis of phased mission systems.

Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains (2019)
Journal Article
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

Due to the high failure rates and the high cost of operation and maintenance of wind turbines, not only manufacturers but also service providers try many ways to improve the reliability of some critical components and subsystems. In reality, redundan... Read More about Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains.

Reliability analysis of general phased mission systems with a new survival signature (2019)
Journal Article
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

It is often difficult for a phased mission system (PMS) to be highly reliable, because this entails achieving high reliability in every phase of operation. Consequently, reliability analysis of such systems is of critical importance. However, efficie... Read More about Reliability analysis of general phased mission systems with a new survival signature.

Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals (2019)
Journal Article
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

In clinical applications, it is important to compare and study the ability of diagnostic tests to discriminate between individuals with and without the disease. In this paper, comparison of two diagnostic tests is presented and discussed using nonpar... Read More about Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals.

Nonparametric Predictive Inference for European Option Pricing based on the Binomial Tree Model (2019)
Journal Article
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

In finance, option pricing is one of the main topics. A basic model for option pricing is the Binomial Tree Model, proposed by Cox, Ross, and Rubinstein in 1979 (CRR). This model assumes that the underlying asset price follows a binomial distribution... Read More about Nonparametric Predictive Inference for European Option Pricing based on the Binomial Tree Model.

A heuristic survival signature based approach for reliability-redundancy allocation (2019)
Journal Article
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

In recent research, the major focus on reliability-redundancy allocation problems has been on the possibility of using more efficient and effective algorithms to improve convergence speed and solution accuracy of the optimization model. But the model... Read More about A heuristic survival signature based approach for reliability-redundancy allocation.

Applying prospect theory to multi-attribute problems with independence assumptions (2019)
Journal Article
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

We discuss a descriptive theory of decision making which has received much attention in recent decades: prospect theory. We specifically focus on applying the theory to problems with two attributes, assisted by different independence assumptions. We... Read More about Applying prospect theory to multi-attribute problems with independence assumptions.

Nonparametric predictive inference for diagnostic test thresholds (2018)
Journal Article
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

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve and surface are useful tools to assess the ability of diagnosti... Read More about Nonparametric predictive inference for diagnostic test thresholds.

System reliability and component importance when components can be swapped upon failure (2018)
Journal Article
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

Resilience of systems to failures during functioning is of great practical importance. One of the strategies that might be considered to enhance reliability and resilience of a system is swapping components when a component fails, thus replacing it b... Read More about System reliability and component importance when components can be swapped upon failure.

Extending the survival signature paradigm to complex systems with non-repairable dependent failures (2018)
Journal Article
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

Dependent failures impose severe consequences on a complex system’s reliability and overall performance, and a realistic assessment, therefore, requires an adequate consideration of these failures. System survival signature opens up a new and efficie... Read More about Extending the survival signature paradigm to complex systems with non-repairable dependent failures.

Imprecise probabilistic inference for software run reliability growth models (2018)
Journal Article
Utkin, L., & Coolen, F. (2018). Imprecise probabilistic inference for software run reliability growth models. Journal of uncertain systems, 12(4), 292-308

This paper presents the application of an inferential statistical approach which combines imprecise Bayesian methods with likelihood inference, to a standard software run reliability growth model. The main idea of the approach is to divide the set of... Read More about Imprecise probabilistic inference for software run reliability growth models.

Approximations for the likelihood ratio statistic for hypothesis testing between two Beta distributions (2018)
Journal Article
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

In this paper, the likelihood ratio to test between two Beta distributions is addressed. The exact distribution of the likelihood ratio statistic, for simple hypotheses, is obtained in terms of Gamma or Generalized Integer Gamma distributions, when t... Read More about Approximations for the likelihood ratio statistic for hypothesis testing between two Beta distributions.

Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests (2018)
Journal Article
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

This paper introduces the nonparametric predictive inference approach for reproducibility of likelihood ratio tests. The general idea of this approach is outlined for tests between two simple hypotheses, followed by an investigation of reproducibilit... Read More about Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests.

Robustness of nonparametric predictive inference for future order statistics (2018)
Journal Article
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

This paper considers robustness of Nonparametric Predictive Inference (NPI), in particular considering inference involving future order statistics. The concept of robust inference is usually aimed at development of inference methods which are not too... Read More about Robustness of nonparametric predictive inference for future order statistics.

Non‐parametric predictive inference for the validation of credit rating systems (2018)
Journal Article
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

Credit rating or credit scoring systems are important tools for estimating the obligor's creditworthiness and for providing an indication of the obligor's future status. The discriminatory power of a credit rating or credit scoring system refers to i... Read More about Non‐parametric predictive inference for the validation of credit rating systems.

Nonparametric predictive inference with parametric copulas for combining bivariate diagnostic tests (2018)
Journal Article
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

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to... Read More about Nonparametric predictive inference with parametric copulas for combining bivariate diagnostic tests.

A robust weighted SVR-based software reliability growth model (2018)
Journal Article
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

This paper proposes a new software reliability growth model (SRGM), which can be regarded as an extension of the non-parametric SRGMs using support vector regression to predict probability measures of time to software failure. The first novelty under... Read More about A robust weighted SVR-based software reliability growth model.

Robust Bayesian reliability for complex systems under prior-data conflict (2018)
Journal Article
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

This paper considers the quantification of system reliability in scenarios in which data, that is, failures or the absence of failures, occurring from the system’s use over time, are considered surprising from the perspective of prior information. A... Read More about Robust Bayesian reliability for complex systems under prior-data conflict.

Nonparametric predictive inference for reproducibility of two basic tests based on order statistics (2018)
Journal Article
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

Reproducibility of statistical hypothesis tests is an issue of major importance in applied statistics: if the test were repeated, would the same overall conclusion be reached, that is rejection or non-rejection of the null hypothesis? Nonparametric p... Read More about Nonparametric predictive inference for reproducibility of two basic tests based on order statistics.

Reliability sensitivity analysis of coherent systems based on survival signature (2018)
Journal Article
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

The reliability sensitivity can be used to rank distribution parameters of system components concerning their impacts on the system’s reliability. Such information is essential to purposes such as component prioritization, reliability improvement, an... Read More about Reliability sensitivity analysis of coherent systems based on survival signature.

Mean residual life of coherent systems consisting of multiple types of dependent components (2018)
Journal Article
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

Mean residual life is a useful dynamic characteristic to study reliability of a system. It has been widely considered in the literature not only for single unit systems but also for coherent systems. This article is concerned with the study of mean r... Read More about Mean residual life of coherent systems consisting of multiple types of dependent components.

Marginal and joint reliability importance based on survival signature (2017)
Journal Article
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

Marginal and joint reliability importance measures have been found to be useful in optimal system design. Various importance measures have been defined and studied for a variety of system models. The results in the literature are mostly based on the... Read More about Marginal and joint reliability importance based on survival signature.

Nonparametric predictive inference for future order statistics (2017)
Journal Article
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

This paper presents nonparametric predictive inference for future order statistics. Given data consisting of n real-valued observations, m future observations are considered and predictive probabilities are presented for the r-th ordered future obser... Read More about Nonparametric predictive inference for future order statistics.

An imprecise statistical method for accelerated life testing using the power-Weibull model (2017)
Journal Article
Yin, Y., 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

Accelerated life testing provides an interesting challenge for quantification of the uncertainties involved, in particular due to the required linking of the units’ failure times, or failure time distributions, at different stress levels. This paper... Read More about An imprecise statistical method for accelerated life testing using the power-Weibull model.

Mixture Models for Prediction from Time Series, with Application to Energy Use Data (2017)
Journal Article
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

This paper aims to use mixture models to produce predictions from time series data. Given data of the form (ti, yi), i = 1, . . . , T , we propose a mix- ture model localized at time point tT with the k-th component as yi = mk (ti) + εik with mixing... Read More about Mixture Models for Prediction from Time Series, with Application to Energy Use Data.

Simulation Methods for System Reliability Using the Survival Signature (2017)
Journal Article
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

Recently, the survival signature has been presented as a summary of the structure function which is sufficient for computation of common reliability metrics and has the crucial advantage that it can be applied to systems with components whose failure... Read More about Simulation Methods for System Reliability Using the Survival Signature.

Optimisation of maintenance policy under parameter uncertainty using portfolio theory (2016)
Journal Article
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

In reliability mathematics, optimisation of maintenance policy is derived based on reliability indexes such as the reliability or its derivatives (e.g., the cumulative failure intensity or the renewal function) and the associated cost information. Th... Read More about Optimisation of maintenance policy under parameter uncertainty using portfolio theory.

On the structure function and survival signature for system reliability (2016)
Journal Article
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 quantification of reliability of systems has, for decades, been based on the structure function, which expresses functioning of a system given the states of its components. One problem of the structure function is that, in its simplest form, for... Read More about On the structure function and survival signature for system reliability.

Bayesian nonparametric system reliability using sets of priors (2016)
Journal Article
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

An imprecise Bayesian nonparametric approach to system reliability with multiple types of components is developed. This allows modelling partial or imperfect prior knowledge on component failure distributions in a flexible way through bounds on the f... Read More about Bayesian nonparametric system reliability using sets of priors.

Nonparametric predictive inference for stock returns (2016)
Journal Article
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

In finance, inferences about future asset returns are typically quantified with the use of parametric distributions and single-valued probabilities. It is attractive to use less restrictive inferential methods, including nonparametric methods which d... Read More about Nonparametric predictive inference for stock returns.

The structure function for system reliability as predictive (imprecise) probability (2016)
Journal Article
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

In system reliability, the structure function models functioning of a system for given states of its components. As such, it is typically a straightforward binary function which plays an essential role in reliability assessment, yet it has received r... Read More about The structure function for system reliability as predictive (imprecise) probability.

k-Boxplots for mixture data (2016)
Journal Article
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

This article introduces a new graphical tool to summarize data which possess a mixture structure. Computation of the required summary statistics makes use of posterior probabilities of class membership which can be obtained from a fitted mixture mode... Read More about k-Boxplots for mixture data.

Predictive inference for bivariate data: Combining nonparametric predictive inference for marginals with an estimated copula (2016)
Journal Article
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

This paper presents a new method for prediction of an event involving a future bivariate observation. The method combines nonparametric predictive inference (NPI) applied to the marginals with a parametric copula to model and estimate the dependence... Read More about Predictive inference for bivariate data: Combining nonparametric predictive inference for marginals with an estimated copula.

Imprecise system reliability and component importance based on survival signature (2016)
Journal Article
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

The concept of the survival signature has recently attracted increasing attention for performing reliability analysis on systems with multiple types of components. It opens a new pathway for a structured approach with high computational efficiency ba... Read More about Imprecise system reliability and component importance based on survival signature.

Imprecise inference for warranty contract analysis (2015)
Journal Article
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

This paper presents an investigation into generalised Bayesian analysis of warranty contracts, using sets of prior distributions within the theory of imprecise probability. Explicit expressions are derived for optimal lower and upper bounds for the e... Read More about Imprecise inference for warranty contract analysis.

A conjugate class of utility functions for sequential decision problems (2015)
Journal Article
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

The use of the conjugacy property for members of the exponential family of distributions is commonplace within Bayesian statistical analysis, allowing for tractable and simple solutions to problems of inference. However, despite a shared motivation,... Read More about A conjugate class of utility functions for sequential decision problems.

Interval estimation for proportional reversed hazard family based on lower record values (2015)
Journal Article
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

This paper explores confidence intervals for the family of proportional reversed hazard distributions based on lower record values. The confidence intervals are validated as long as the sample is of size n≥3. The proposed procedure can be extended to... Read More about Interval estimation for proportional reversed hazard family based on lower record values.

Predictive inference for system reliability after common-cause component failures (2014)
Journal Article
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

This paper presents nonparametric predictive inference for system reliability following common-cause failures of components. It is assumed that a single failure event may lead to simultaneous failure of multiple components. Data consist of frequencie... Read More about Predictive inference for system reliability after common-cause component failures.

Nonparametric Predictive Inference with Combined Data Under Different Right-Censoring Schemes (2014)
Journal Article
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

This paper presents nonparametric predictive inference (NPI) for meta-analysis in which multiple independent samples of lifetime data are combined, where different censoring schemes may apply to the different samples. NPI is a frequentist statistical... Read More about Nonparametric Predictive Inference with Combined Data Under Different Right-Censoring Schemes.

Bayesian inference for reliability of systems and networks using the survival signature (2014)
Journal Article
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

The concept of survival signature has recently been introduced as an alternative to the signature for reliability quantification of systems. While these two concepts are closely related for systems consisting of a single type of component, the surviv... Read More about Bayesian inference for reliability of systems and networks using the survival signature.

Nonparametric predictive inference for system reliability using the survival signature (2014)
Journal Article
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

The survival signature has recently been presented as an attractive concept to aid quantification of system reliability. It has similar characteristics as the system signature, which is well established, but contrary to the latter it is easily applic... Read More about Nonparametric predictive inference for system reliability using the survival signature.

Three-group ROC analysis: a nonparametric predictive approach (2014)
Journal Article
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

Measuring the accuracy of diagnostic tests is crucial in many application areas, in particular medicine and health care. The receiver operating characteristic (ROC) surface is a useful tool to assess the ability of a diagnostic test to discriminate a... Read More about Three-group ROC analysis: a nonparametric predictive approach.

Classification with support vector machines and Kolmogorov-Smirnov bounds (2014)
Journal Article
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

This article presents a new statistical inference method for classification. Instead of minimizing a loss function that solely takes residuals into account, it uses the Kolmogorov–Smirnov bounds for the cumulative distribution function of the residua... Read More about Classification with support vector machines and Kolmogorov-Smirnov bounds.

Classification with decision trees from a nonparametric predictive inference perspective (2014)
Journal Article
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

An application of nonparametric predictive inference for multinomial data (NPI) to classification tasks is presented. This model is applied to an established procedure for building classification trees using imprecise probabilities and uncertainty me... Read More about Classification with decision trees from a nonparametric predictive inference perspective.

Nonparametric predictive inference for combined competing risks data (2014)
Journal Article
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

The nonparametric predictive inference (NPI) approach for competing risks data has recently been presented, in particular addressing the question due to which of the competing risks the next unit will fail, and also considering the effects of unobser... Read More about Nonparametric predictive inference for combined competing risks data.

Maximum group sizes for simultaneous testing in high potential risk scenarios (2013)
Journal Article
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

When tests are performed in scenarios such as reliability demonstration, two extreme possibilities are to perform all required tests simultaneously or to test all units sequentially. From the perspective of time for testing, the former is typically p... Read More about Maximum group sizes for simultaneous testing in high potential risk scenarios.

Nonparametric predictive inference for system failure time based on bounds for the signature (2013)
Journal Article
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

System signatures provide a powerful framework for reliability assessment for systems consisting of exchangeable components. The use of signatures in nonparametric predictive inference has been presented and leads to lower and upper survival function... Read More about Nonparametric predictive inference for system failure time based on bounds for the signature.

Nonparametric predictive multiple comparisons of lifetime data (2012)
Journal Article
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

We consider lifetime experiments to compare units from different groups, where the units’ lifetimes may be right censored. Nonparametric predictive inference for comparison of multiple groups is presented, in particular lower and upper probabilities... Read More about Nonparametric predictive multiple comparisons of lifetime data.

Nonparametric predictive inference for binary diagnostic tests (2012)
Journal Article
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

Measuring the accuracy of diagnostic tests is crucial in many application areas, including medicine, health care, and data mining. Good methods for determining diagnostic accuracy provide useful guidance on selection of patient treatment, and the abi... Read More about Nonparametric predictive inference for binary diagnostic tests.

Nonparametric predictive inference for failure times of systems with exchangeable components (2012)
Journal Article
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

The theory of system signatures (Samaniego, 2007) provides a powerful framework for reliability assessment for systems consisting of exchangeable components. For a system with m components, the signature is a vector containing the probabilities for t... Read More about Nonparametric predictive inference for failure times of systems with exchangeable components.

Nonparametric predictive inference for diagnostic accuracy (2012)
Journal Article
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

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. Good methods for determining diagnostic accuracy provide useful guidance on selection of patient treatment, and the ability to compare... Read More about Nonparametric predictive inference for diagnostic accuracy.

Unobserved, re-defined, unknown or removed failure modes in competing risks (2011)
Journal Article
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

Recently the nonparametric predictive approach to inference for competing risks was introduced by Maturi et al. (2010, J. Risk Reliab. 224, 11–26). In this paper further results for such inferences are presented, with focus on four important and clos... Read More about Unobserved, re-defined, unknown or removed failure modes in competing risks.

Imprecision in Statistical Theory and Practice (2009)
Journal Article
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 (2009)
Journal Article
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

Imprecise probabilistic methods in reliability provide exciting opportunities for dealing with partial observations and incomplete knowledge on dependencies in failure data. In this paper, we explore the use of the imprecise Dirichlet model for deali... Read More about Applying the imprecise Dirichlet model in cases with partial observations and dependencies in failure data.

Nonparametric predictive comparison of proportions (2007)
Journal Article
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

We use the lower and upper predictive probabilities from Coolen [1998. Low structure imprecise predictive inference for Bayes’ problem. Statist. Probab. Lett. 36, 349–357] to compare future numbers of successes in Bernoulli trials for different group... Read More about Nonparametric predictive comparison of proportions.

On nonparametric predictive inference and abjective Bayesianism (2006)
Journal Article
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

This paper consists of three main parts. First, we give an introduction to Hill’s assumption A (n) and to theory of interval probability, and an overview of recently developed theory and methods for nonparametric predictive inference (NPI), which is... Read More about On nonparametric predictive inference and abjective Bayesianism.

Nonparametric adaptive opportunity-based replacement strategies (2006)
Journal Article
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

We consider opportunity-based age replacement (OAR) using nonparametric predictive inference (NPI) for the time to failure of a future unit. Based on n observed failure times, NPI provides lower and upper bounds for the survival function for the time... Read More about Nonparametric adaptive opportunity-based replacement strategies.

Bayesian reliability demonstration with multiple independent tasks. (2005)
Journal Article
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

We consider optimal testing of a system in order to demonstrate reliability with regard to its use in a process after testing, where the system has to function for different types of tasks, which we assume to be independent. We explicitly assume that... Read More about Bayesian reliability demonstration with multiple independent tasks..

Bayesian reliability demonstration for failure-free periods (2005)
Journal Article
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

We study sample sizes for testing as required for Bayesian reliability demonstration in terms of failure-free periods after testing, under the assumption that tests lead to zero failures. For the process after testing, we consider both deterministic... Read More about Bayesian reliability demonstration for failure-free periods.

Nonparametric predictive inference with right-censored data (2004)
Journal Article
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

We present a new method of statistical inference for data that include right-censored observations. The method is based on Hill's A(n), a generalization of this assumption is introduced explicitly to deal with right-censored observations. We derive b... Read More about Nonparametric predictive inference with right-censored data.

Nonparametric predictive inference and interval probability (2004)
Journal Article
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

The assumption A(n), proposed by Hill (J. Amer. Statist. Assoc. 63 (1968) 677), provides a natural basis for low structure non-parametric predictive inference, and has been justified in the Bayesian framework. This paper embeds A(n)-based inference i... Read More about Nonparametric predictive inference and interval probability.

A nonparametric predictive method for queues. (2003)
Journal Article
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

This paper presents a novel statistical approach to queues. Instead of studying characteristics of an assumed parametric stochastic model, the method uses information in the form of observed service times per queue and, while adding a minimum of addi... Read More about A nonparametric predictive method for queues..

Nonparametric predictive inference in reliability. (2002)
Journal Article
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

We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data,... Read More about Nonparametric predictive inference in reliability..

Bayesian Graphical Models for Software Testing (2002)
Journal Article
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

This paper describes a new approach to the problem of software testing. The approach is based on Bayesian graphical models and presents formal mechanisms for the logical structuring of the software testing problem, the probabilistic and statistical t... Read More about Bayesian Graphical Models for Software Testing.

Condition monitoring: a new perspective (2000)
Journal Article
Coolen, F., & Coolen-Schrijner, P. (2000). Condition monitoring: a new perspective. Journal of the Operational Research Society, 51, 311-319