Article
Engineering, Mechanical
A. Tridello, C. Boursier Niutta, F. Berto, M. M. Tedesco, S. Plano, D. Gabellone, D. S. Paolino
Summary: In this study, three methodologies for estimating fatigue design P-S-N curves are compared. Experimental validation shows that all three methods provide reliable estimations of the design curves, and the test duration and data requirements can be significantly reduced with appropriate testing strategies.
INTERNATIONAL JOURNAL OF FATIGUE
(2022)
Article
Engineering, Multidisciplinary
Tahira Kanwal, Kamran Abbas
Summary: In this paper, Bayesian estimators, Jeffery's priors, and maximum likelihood estimators are used to estimate the unknown parameters of process capability indices in the Fréchet distribution. Bootstrap confidence intervals are developed based on these estimators. Monte Carlo simulations are performed to evaluate the performance of the indices for small, moderate, and large sample sizes using skewness, kurtosis, mean square error, and intervals' widths. Simulation results show that the Bayesian estimator under reference prior outperforms in small sample sizes and all methods perform equally well in larger sample sizes. The average width for the bootstrap confidence interval for Cs is the narrowest. Real data analysis is conducted for illustration purposes.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2023)
Article
Engineering, Multidisciplinary
Samuel Rosa, Andrea Kocianova
Summary: This paper addresses the issue of accuracy in estimating critical gaps at unsignalized intersections, providing new methods for measuring the accuracy of such estimates and offering guidance on the number of observations required for reliable results.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Statistics & Probability
M. S. Kotb, M. Z. Raqab
Summary: This paper focuses on estimating the reliability of a multi-component stress-strength model in an s-out-m system under progressively type-II censored modified Weibull data. Maximum likelihood and Bayes estimators are used, along with the development of confidence and credible intervals. The Lindley's approximation and Markov chain Monte Carlo methods are applied for computing approximate Bayes estimates and analyzing two real data sets.
STATISTICAL PAPERS
(2021)
Article
Computer Science, Interdisciplinary Applications
Nabakumar Jana, Samadrita Bera
Summary: This study considers interval estimation of stress-strength reliability using inverse Weibull distributions for stress and strength components. HPD credible intervals, generalized confidence intervals, and bootstrap confidence intervals are proposed for different shape parameter scenarios. Monte Carlo simulations and real data examples demonstrate the practicality of these methods.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Multidisciplinary Sciences
Wisunee Puggard, Sa-Aat Niwitpong, Suparat Niwitpong
Summary: This study introduces four methods for constructing confidence intervals for the coefficient of variation (CV) and the difference between CVs of Birnbaum-Saunders (BS) distributions. A Monte Carlo simulation shows that the highest posterior density (HPD) interval performs best overall. The proposed methods were validated using PM 2.5 concentration data for Chiang Mai, Thailand in March and April 2019, with results consistent with the simulation findings.
Article
Multidisciplinary Sciences
Matthew Stephens
Summary: This article discusses the benefits of adopting a "Bayesian lens" approach to non-Bayesian methods and warns against the dangers of exclusively using Bayesian methods due to philosophical principles. It aims to help scientists, statistics teachers, and practitioners understand commonly used statistical methods and strike a balance between philosophy and practicality.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Article
Mathematics
Caner Tanis, Bugra Saracoglu, Akbar Asgharzadeh, Meraj Abdi
Summary: This study addresses the estimation problem of stress-strength reliability R = Pr( X < Y) based on upper record values for exponential power distribution. We employ maximum likelihood and Bayes methods to estimate R. The Tierney-Kadane approximation is used for the Bayes estimation of R due to the lack of analytical solution. Asymptotic confidence interval is derived based on the asymptotic distribution of the maximum likelihood estimator of R. A Monte Carlo simulation study is conducted to compare the performances of maximum likelihood estimators and Bayes estimators using mean square error criteria. Finally, a real data application is presented.
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
(2023)
Article
Statistics & Probability
Sara Ghanbari, Abdolhamid Rezaei Roknabadi, Mahdi Salehi
Summary: This study focuses on estimating the stress-strength parameter R in the context of the Marshall-Olkin model and progressively Type-II censored samples, using the exponential distribution for simplification and applying maximum likelihood and Bayesian methods for estimation. Bayesian estimators of R are obtained using Lindley's approximation and Gibbs sampling methods, as explicit forms cannot be obtained. Confidence intervals of various types for R are derived and compared via Monte Carlo simulation. The survival times of head and neck cancer patients under two therapies are analyzed to illustrate the methods.
JOURNAL OF APPLIED STATISTICS
(2022)
Article
Statistics & Probability
Mojammel Haque Sarkar, Manas Ranjan Tripathy, Debasis Kundu
Summary: This study considers the estimation of parameters for the generalized inverse Lindley (GIL) distribution and proposes point estimators and Bayesian estimators. It also introduces various confidence interval methods and prediction methods, which are evaluated and validated through simulation studies and real-life datasets.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2022)
Article
Engineering, Multidisciplinary
Mayank Kumar Jha, Sanku Dey, Refah Alotaibi, Ghadah Alomani, Yogesh Mani Tripathi
Summary: This paper considers the estimation of stress-strength reliability using both frequentist and Bayesian methods when both stress and strength variables follow unit generalized exponential distributions. The frequentist methods include maximum likelihood, least squares, weighted least squares, and maximum product spacing methods. The Bayesian methods use gamma and weighted Lindley priors for model parameters. Monte-Carlo simulation studies are conducted to evaluate the performance of the proposed estimates, and an engineering dataset is analyzed to demonstrate the applicability of the methods.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Statistics & Probability
Sanku Dey, Liang Wang, Mazen Nassar
Summary: This paper presents methods of estimation of parameters and acceleration factor for Nadarajah-Haghighi distribution based on constant-stress partially accelerated life tests, and conducts simulation studies and data analysis to confirm their effectiveness.
JOURNAL OF APPLIED STATISTICS
(2022)
Article
Quantum Science & Technology
Alfred Godley, Madalin Guta
Summary: In this paper, the problem of extracting maximum information from continuous-time measurements in quantum systems is addressed. The authors propose an efficient algorithm for optimal estimation of one-dimensional dynamical parameters in discrete-time input-output quantum Markov chains. The algorithm involves updating a "measurement filter" operator and determining measurement bases for the output units. A key component of the algorithm is the use of a coherent quantum absorber to "post-process" the output. The scheme offers potential for optimal continuous-time adaptive measurements, but practical implementations require further research.
Article
Engineering, Industrial
Yogesh Mani Tripathi, C. Petropoulos, Mayank Kumar Jha
Summary: This paper considers the problem of estimating a stress-strength parameter under the assumption that both stress and strength variables follow independent lognormal distributions. The estimation and interval estimation of the parameter are obtained through methods such as maximum likelihood estimation and Bayesian estimation, and numerical comparisons and analysis of real data sets are conducted.
QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT
(2022)
Article
Engineering, Chemical
Ahmed Ibrahim Shawky, Khushnoor Khan
Summary: The present study focuses on the multi-component stress-strength model based on inverse Weibull distribution. Reliability is obtained using the maximum likelihood method, and the performance of different sample sizes and parameter combinations on reliability is compared using Monte Carlo simulation. A real data set is used to demonstrate the application of the proposed technique in studying the strength and stress of a multicomponent model.
Article
Statistics & Probability
Jazaa S. Al-Mutairi, Mohammad Z. Raqab
STATISTICAL PAPERS
(2020)
Article
Statistics & Probability
Mohammad Z. Raqab, Omar M. Bdair, Manoj K. Rastogi, Fahad M. Al-aboud
Summary: In this paper, estimation of unknown parameters using frequentist and Bayesian approaches from a hybrid censored sample of a two parameter exponentiated half logistic distribution is considered. Various algorithms were used to obtain point estimators and confidence intervals for the shape and scale parameters, and data analyses on cancer patients' survival times were conducted. A numerical simulation study was carried out to evaluate the developed methods and conclusions on the findings were reported.
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2021)
Article
Statistics & Probability
Mohammad Z. Raqab, Debasis Kundu, Fahimah A. Al-Awadhi
Summary: This study introduces a compound zero-truncated Poisson normal distribution and a four-parameter bivariate distribution with continuous and discrete marginals. It discusses estimation of unknown parameters using an EM type algorithm, and assesses the effectiveness of the algorithm through simulation experiments and analysis of a real data set.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Statistics & Probability
Heba A. Almuzaini, Mohammad Z. Raqab
Summary: The performances of different point predictors of future record data are studied based on informative records from the two-parameter exponential distribution, with a focus on Pitman's measure of closeness. The best unbiased and conditional median predictors are found to be competitive in terms of Pitman closeness when compared to other predictors.
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2022)
Article
Statistics & Probability
Adeleh Fallah, Akbar Asgharzadeh, Hon Keung Tony Ng
Summary: This paper develops tools for statistical inference of lifetime distribution in coherent systems, discussing the existence and uniqueness of maximum likelihood estimator and proposing two statistical testing procedures. Illustrative numerical examples and Monte Carlo simulations are used for explanation and evaluation of the methods.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Statistics & Probability
Elham Basiri, Arturo J. Fernandez, Akbar Asgharzadeh, Seyed Fazel Bagheri
Article
Engineering, Multidisciplinary
Abduallah M. Almarashi, Ali Algarni, A. M. Daghistani, G. A. Abd-Elmougod, S. Abdel-Khalek, Mohammad Z. Raqab
Summary: This paper addresses the problem of comparative life tests under joint censoring samples from an exponential distribution with competing risks model, focusing on two causes of failure and units from two production lines censored under a hybrid progressive Type-I censoring scheme. Maximum likelihood estimation, different Bayes methods, asymptotic confidence intervals, and Bayes credible intervals are discussed, with a real data set analyzed for illustrative purposes. Theoretical results are evaluated and compared through Monte Carlo studies.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Statistics & Probability
Husam A. Bayoud, Mohammad Z. Raqab
Summary: This article investigates the joint Type-II progressive censoring scheme for two populations with lifetimes following Topp-Leone models, but with unknown parameters. Classical and Bayesian inferences are used to estimate the parameters, and Monte Carlo simulation is conducted to compare the performance of the methods.
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2021)
Article
Automation & Control Systems
Mohammad Z. Raqab, Husam A. Bayoud, Guoxin Qiu
Summary: The information content of a random variable is studied in the field of information theory. The mean and variance of the information content are referred to as entropy and varentropy, respectively. This paper focuses on the varentropy of the inactivity time of a random variable, termed as past varentropy. Reliability properties associated with the past varentropy and the reversed hazard rate function are discussed. Lower and upper bounds for the past varentropy are provided. The varentropy is applied to the proportional reversed hazard rate model. Furthermore, an asymptotic distribution for the information content of the inactivity time is derived based on past entropy and varentropy.
IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohammed A. Meraou, Noriah M. Al-Kandari, Mohammad Z. Raqab, Debasis Kundu
Summary: This paper introduces a new family of distributions, the compound zero-truncated Poisson exponential distribution, for analyzing skewed data. It proposes an algorithm for parameter estimation and considers a bivariate version of the model. Through simulation studies and analysis of real data, the performance and effectiveness of the proposed models are verified.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
(2022)
Article
Statistics & Probability
Omar M. Bdair, Mohammad Z. Raqab
Summary: The study focuses on predicting unobserved censored units from a mixture exponential distribution with unknown parameters, proposing different prediction methods and considering two scenarios of sample size. The parametric bootstrap-based prediction intervals are shown to be comparable in coverage probability and competitive in average length compared to other methods.
Article
Computer Science, Hardware & Architecture
S. F. Bagheri, A. Asgharzadeh, Arturo J. Fernandez, Carlos J. Perez-Gonzalez
Summary: This study investigates the construction of prediction sets for future failure times based on a type-II censored sample from the exponential distribution. Balanced prediction sets and a constrained optimization problem are used to determine the prediction region with minimal area. Monte Carlo simulation and real data examples are provided to compare the performance and illustrate the methods, with discussions on applications and extensions of the results.
IEEE TRANSACTIONS ON RELIABILITY
(2022)
Article
Statistics & Probability
M. A. Meraou, N. M. Al-Kandari, M. Z. Raqab
Summary: In this article, a new compound zero-truncated Poisson gamma model is proposed and its mathematical properties are discussed. The model is shown to be convenient to implement and can be extended to a four-parameter bivariate model. Experiment results and analysis of real data demonstrate the flexibility of the proposed models.
JOURNAL OF STATISTICAL THEORY AND PRACTICE
(2022)
Article
Engineering, Multidisciplinary
Mohammad A. Amleh, Mohammad Z. Raqab
Summary: This paper investigates a simple step-stress model based on type-II censoring Weibull lifetimes, using KH model to develop Bayesian approaches for estimating model parameters and predicting future times to failure. The main goals of this work include parameter estimation and the study of posterior predictive density.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2023)
Article
Mathematics, Applied
M. Alizadeh, A. Asgharzadeh, E. Basiri
Summary: This paper discusses the problem of missing middle lifetimes in reliability studies and proposes a method for reconstructing the unobserved lifetimes. By finding balanced reconstruction regions and using constrained minimization problem, the reconstruction regions are obtained. A simulation study and two numerical examples are presented for illustrative and comparative purposes.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2024)
