|
|
|
|
|
 |
Search published articles |
 |
|
Showing 6 results for Reversed Hazard Rate
Nahid Sanjari Farsipour, Hajar Riyahi,
Volume 7, Issue 2 (3-2014)
Abstract
In this paper the likelihood and Bayesian inference of the stress-strength reliability are considered based on record values from proportional and proportional reversed hazard rate models. Then inference of the stress-strength reliability based on lower record values from some generalized distributions are also considered. Next the likelihood and Bayesian inference of the stress-strength model based on upper record values from Gompertz, Burr type XII, Lomax and Weibull distributions are considered. The ML estimators and their properties are studied. Likelihood-based confidence intervals, exact, as well as the Bayesian credible sets and bootstrap interval for the stress-strength reliability in all distributions are obtained. Simulation studies are conducted to investigate and compare the performance of the intervals.
Ghobad Barmalzan, Abedin Haidari, Khaled Masomifard,
Volume 9, Issue 2 (2-2016)
Abstract
In this paper, series and parallel systems, when the lifetimes of their components following the scale model are studied and different stochastic orderings between them are discussed. Moreover, we apply these results to the series and parallel systems consisting of exponentiated Weibull or generalized gamma components. The presented results in this paper complete and extend some known results in the literature.
Nader Nematollahi,
Volume 10, Issue 2 (2-2017)
Abstract
In some applied problems we need to choose a population from the given populations and estimate the parameter of the selected population. Suppose k random samples are chosen from k populations with proportional hazard rate model or proportional reversed hazard rate model. According to a specified selection rule, it is desired to estimate the parameter of the best (worst) selected population. In this paper, under the entropy loss function we obtain the uniformly minimum risk unbiased (UMRU) estimator of the parameters of the selected population, and derived sufficient conditions for minimaxity of a given estimator. Then we find the class of admissible and inadmissible linear estimators of the parameters of the selected population and determine the class of dominators of a given estimator. We show that the UMRU estimator is inadmissible and compare the obtained estimators by plotting their risk functions.
Shahrokh Hashemi-Bosra, Ebrahim Salehi,
Volume 11, Issue 1 (9-2017)
Abstract
The (n-k+1)-out-of-n systems are important types of coherent systems and have many applications in various areas of engineering. In this paper, the general inactivity time of failed components of (n-k+1)-out-of-n system is studied when the system fails at time t>0. First we consider a parallel system including two exchangeable components and then using Farlie-Gumbel-Morgenstern copula, investigate the behavior of mean inactivity time of failed components of the system. In the next part, (n-k+1)-out-of-n systems with exchangeable components are considered and then, some stochastic ordering properties of the general inactivity time of the systems are presented based on one sample or two samples.
Ghobad Barmalzan,
Volume 12, Issue 2 (3-2019)
Abstract
The aggregate claim amount in a particular time period is a quantity of fundamental importance for proper management of an insurance company and also for pricing of insurance coverages. In this paper, the usual stochastic order between aggregate claim amounts is discussed when the survival function of claims is a increasing and concave. The results established here complete some results of Li and Li (2016).
Jafar Ahmadi, Fatemeh Hooti,
Volume 13, Issue 2 (2-2020)
Abstract
In survival studies, frailty models are used to explain the unobserved heterogeneity hazards. In most cases, they are usually considered as the product of the function of the frailty random variable and baseline hazard rate. Which is useful for right censored data. In this paper, the frailty model is explained as the product of the frailty random variable and baseline reversed hazard rate, which can be used for left censored data. The general reversed hazard rate frailty model is introduced and the distributional properties of the proposed model and lifetime random variables are studied. Some dependency properties between lifetime random variable and frailty random variable are investigated. It is shown that some stochastic orderings preserved from frailty random variables to lifetime variables. Some theorems are used to obtain numerical results. The application of the proposed model is discussed in the analysis of left censored data. The results are used to model lung cancer data.
|
|
|
|
|
|
|
|
|
|
|
