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Showing 22 results for Hazard Rate
Ghobad Barmalzan, Abedin Haidari, Maryam Abdollahzade,
Volume 6, Issue 2 (2-2013)
Abstract
Suppose there are two groups of independent exponential random variables, where the first group has different hazard rates and the second group has common hazard rate. In this paper, the various stochastic orderings between their sample spacings have studied and introduced some necessary and sufficient conditions to equivalence of these stochastic ordering. Also, for the special case of sample size two, it is shown that the hazard rate function of the second sample spacing is Shcur-concave in the inverse vector of parameters.
Ghobad Barmalzan, Abedin Heidari,
Volume 7, Issue 1 (9-2013)
Abstract
Suppose there are two groups of random variables, one with independent and non-identical distributed and another with independent and identical distributed. In this paper, for the case when the size of groups are not equal, and all of the underlying random variables have exponential distribution, the necessary and sufficient conditions are obtained for establishing the mean residual life, hazard rate and dispersive orders between the second order statistics of two groups. Moreover, when random variables follow the Weibull distribution, the hazard rate, dispersive and likelihood ratio order between the second order statistics from two groups are investigated.
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.
Aref Khanjari Idenak, Mohammadreza Zadkarami, Alireza Daneshkhah,
Volume 8, Issue 2 (3-2015)
Abstract
In this paper a new compounding distribution with increasing, decreasing, bathtub shaped and unimodal hazard rate function is proposed. The new four-parameters distribution is a generalization of the complementary exponential power distribution. The raw-moments, density function of the order statistics, survival function, hazard rate function, quantiles, mean residual lifetime and reliability function are presented. The estimation of the new distribution in a special case Poisson complementary exponential power distribution is studied by the method of maximum likelihood and EM algorithm. Expression for asymptotic distribution for the maximum likelihood estimation of the parameters of the PCEP distribution are obtained and for determining the precision of the variance and covariance of the estimations, a simulation is used, Then experimental results are illustrated based on the real data set.
Shahram Yaghoubzadeh, Ali Shadrokh, Masoud Yarmohammadi,
Volume 9, Issue 1 (9-2015)
Abstract
In this paper, we introduce a new five-parameters distribution with increasing, decreasing, bathtub-shaped failure rate, called as the Beta Weibull-Geometric (BWG) distribution. Using the Sterling Polynomials, the probability density function and several properties of the new distribution such as its reliability and failure rate functions, quantiles and moments, Renyi and Shannon entropies, moments of order statistics, mean residual life, reversed mean residual life are obtained. The maximum likelihood estimation procedure is presented in this paper. Also, we compare the results of fitting this distribution to some of their sub-models, using to a real data set. It is also shown that the BWG distribution fits better to this data set.
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.
Eisa Mahmoudi, Somayeh Abolhosseini,
Volume 10, Issue 1 (8-2016)
Abstract
In this paper we propose a new two-parameters distribution, which is an extension of the Lindley distribution with increasing and bathtub-shaped failure rate, called as the Lindley-logarithmic (LL) distribution. The new distribution is obtained by compounding Lindley (L) and Logarithmic distributions. We obtain several properties of the new distribution such as its probability density function, its failure rate functions, quantiles and moments. The maximum likelihood estimation procedure via a EM-algorithm is presented in this paper. At the end, in order to show the flexibility and potentiality of this new class, some series of real data is used to fit.
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).
Ghobad Barmalzan,
Volume 13, Issue 1 (9-2019)
Abstract
In this paper, under certain conditions, the usual stochastic, convex and dispersive orders between the smallest claim amounts with independent Weibull claims are discussed. Also, under conditions on some well-known common copula, some stochastic comparisons of smallest claim amounts with dependent heterogeneous claims have been obtained.
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.
Mohadaseh Khayyat, Rasool Rozegar, Ghobad Barmalzan,
Volume 14, Issue 1 (8-2020)
Abstract
The modified proportional hazard rates model, as one of the flexible families of distributions in reliability and survival analysis, and stochastic comparisons of (n-k+1) -out-of- n systems comprising this model have been introduced by Balakrishnan et al. (2018). In this paper, we consider the modified proportional hazard rates model with a discrete baseline case and investigate ageing properties and preservation of the usual stochastic order, hazard rate order and likelihood ratio order in this family of distributions.
Seyede Toktam Hosseini, Jafar Ahmadi,
Volume 14, Issue 2 (2-2021)
Abstract
In this paper, using the idea of inaccuracy measure in the information theory, the residual and past inaccuracy measures in the bivariate case are defined based on copula functions. Under the assumption of radial symmetry, the equality of these two criteria is shown, also by the equality between these two criteria, radially symmetrical models are characterized. A useful bound is provided by establishing proportional (inverse) hazard rate models for marginal distributions. Also, the proportional hazard rate model in bivariate mode is characterized by assuming proportionality between the introduced inaccuracy and its corresponding entropy. In addition, orthant orders are used to obtain inequalities. To illustrate the results, some examples and simulations are presented.
Mojtaba Esfahani, Mohammad Amini, Gholamreza Mohtashami Borzadaran,
Volume 15, Issue 1 (9-2021)
Abstract
In this article, the total time on test (TTT) transformation and its major properties are investigated. Then, the relationship between the TTT transformation and some subjects in reliability theory is expressed. The TTT diagram is also drawn for some well-known lifetime distributions, and a real-data analysis is performed based on this diagram. A new distorted family of distributions is introduced using the distortion function. The statistical interpretation of the new life distribution from the perspective of reliability is provided, and its survival function is derived. Finally, a generalization of the Weibull distribution is introduced using a new distortion function. A real data analysis shows its superiority in fitting in comparison to the traditional Weibull model.
Ghobad Barmalzan, Ali Akbar Hosseinzadeh, Ebrahim Amini Seresht,
Volume 15, Issue 2 (3-2022)
Abstract
This paper discusses the hazard rate order of the fail-safe systems arising from two sets of independent multiple-outlier scale distributed components. Under certain conditions on scale parameters in the scale model and the submajorization order between the sample size vectors, the hazard rate ordering between the corresponding fail-safe systems from multiple-outlier scale random variables is established. Under certain conditions on the Archimedean copula and scale parameters, we also discuss the usual stochastic order of these systems with dependent components.
Ebrahim Amini-Seresht, Ghobad Barmalzan, Ebrahim Nasiroleslami,
Volume 16, Issue 1 (9-2022)
Abstract
This paper deals with some stochastic comparisons of convolution of random variables comprising scale variables. Sufficient conditions are established for these convolutions' likelihood ratio ordering and hazard rate order. The results established in this paper generalize some known results in the literature. Several examples are also presented for more illustrations.
Aliakbar Hosseinzadeh, Ghobad Barmalzan, Mostafa Sattari,
Volume 16, Issue 1 (9-2022)
Abstract
In this paper, we discuss the hazard rate order of (n-1)-out-of-n systems arising from two sets of independent multiple-outlier modified proportional hazard rates components. Under certain conditions on the parameters and the sub-majorization order between the sample size vectors, the hazard rate order between the (n-1)-out-of-n systems from multiple-outlier modified proportional hazard rates is established.
Jalal Etminan, Mohammad Khanjari Sadegh, Maid Chahkandi,
Volume 16, Issue 2 (3-2023)
Abstract
This paper considers series and parallel systems with independent and identically distributed component lifetimes. The reliability of these systems can be improved by using the reduction method. In the reduction method, system reliability is increased by reducing the failure rates of some of its components by a factor 0<ρ<1, called the equivalent reliability factor. Closed formulas are obtained for some reliability equivalence factors. In comparisons among the performance of the systems, these factors are helpful. We discuss that the reduction method can be considered as a particular case of the proportional hazard rates (PHR) model. Sufficient conditions for the relative aging comparison of the improved series and parallel systems under the PHR model and reduction method are also developed.
Aqeel Lazam Razzaq, Isaac Almasi, Ghobad Saadat Kia,
Volume 18, Issue 2 (2-2025)
Abstract
Adding parameters to a known distribution is a valuable way of constructing flexible families of distributions. In this paper, we introduce a new model, the modified additive hazard rate model, by replacing the additive hazard rate distribution in the general proportional add ratio model. Next, when two sets of random variables follow the modified additive hazard model, we establish stochastic comparisons between the series and parallel systems comprising these components.
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