The exponentiated half-logistic distribution has various shapes depending on its shape parameter. Therefore, this paper proposes more efficient approach methods for estimating shape parameters in the presence of a nuisance parameter, that is, a scale parameter, from Bayesian and non-Bayesian perspectives if record values have an exponentiated half-logistic distribution. In the frequentist approach, estimation methods based on pivotal quantities are proposed which require no complex computation unlike the maximum likelihood method. In the Bayesian approach, a robust estimation method is developed by constructing a hierarchical structure of the parameter of interest. In addition, two approaches address how the nuisance parameter can be dealt with and verifies that the proposed methods are more efficient than existing methods through Monte Carlo simulations and analyses based on real data.
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http://dx.doi.org/10.1186/s40064-016-3047-y | DOI Listing |
PLoS One
January 2025
Department of Statistics, University of Kerala, Trivandrum, India.
This paper presents a novel extension of the exponentiated inverse Rayleigh distribution called the half-logistic exponentiated inverse Rayleigh distribution. This extension improves the flexibility of the distribution for modeling lifetime data for both monotonic and non-monotonic hazard rates. The statistical properties of the half-logistic exponentiated inverse Rayleigh distribution, such as the quantiles, moments, reliability, and hazard function, are examined.
View Article and Find Full Text PDFJ Appl Stat
May 2024
Department of Statistics, Shanghai University Of Finance and Economics ZheJiang College, Jinhua, People's Republic of China.
Numerous studies have solved the problem of monitoring statistical processes with complete samples. However, censored or incomplete samples are commonly encountered due to constraints such as time and cost. Adaptive progressive Type II hybrid censoring is a novel method with the advantages of saving time and improving efficiency.
View Article and Find Full Text PDFJ Appl Stat
April 2024
Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh, India.
In survival analysis, the Accelerated Failure Time (AFT) shared frailty model is a widely used framework for analyzing time-to-event data while accounting for unobserved heterogeneity among individuals. This paper extends the traditional Weibull AFT shared frailty model using half logistic-G family of distributions (Type I, Type II and Type II exponentiated) through Bayesian methods. This approach offers flexibility in capturing covariate influence and handling heavy-tailed frailty distributions.
View Article and Find Full Text PDFHeliyon
September 2024
Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia.
A new distribution, the type II exponentiated half logistic-odd Burr X-G power series (TII-EHL-OBX-GPS), is introduced in this study. This distribution combines the type II exponentiated half logistic-odd Burr X-G family of distributions with power series distributions. We discuss its mathematical characteristics, maximum likelihood estimates and simulation experiments, along with practical applications in the type II exponentiated half logistic-odd Burr X-log-logistic Poisson distribution.
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