scholarly journals Comparison of two sampling schemes in estimating the stress-strength reliability under the proportional reversed hazard rate model

2020 ◽  
Vol 9 (1) ◽  
pp. 82-98
Author(s):  
Amineh Sadeghpour ◽  
Ahmad Nezakati ◽  
Mahdi Salehi
Keyword(s):  
Hazard Rate ◽  
Interval Estimation ◽  
Minimum Variance ◽  
Ranked Set Sampling ◽  
Sampling Scheme ◽  
Rate Model ◽  
Data Set ◽  
Reversed Hazard Rate ◽  
Sampling Schemes ◽  
Hazard Rate Model

In this paper, point and interval estimation of stress-strength reliability based on lower record ranked set sampling scheme under the proportional reversed hazard rate model are considered. Maximum likelihood, uniformly minimum variance unbiased, and Bayesian estimators of $\mathcal{R}$ are derived and their performances are compared. Various confidence intervals for the parameter $\mathcal{R}$ are constructed, and compared based on the simulation study. Moreover, the record ranked set sampling scheme is compared with ordinary records in case of interval estimations. Finally, a data set has been analyzed for illustrative purposes.

Stochastic comparisons of largest-order statistics for proportional reversed hazard rate model and applications

2020 ◽  
Vol 57 (3) ◽  
pp. 832-852
Author(s):  
Lu Li ◽  
Qinyu Wu ◽  
Tiantian Mao
Keyword(s):  
Order Statistics ◽  
Likelihood Ratio ◽  
Hazard Rate ◽  
Parallel Systems ◽  
Rate Model ◽  
Stochastic Comparisons ◽  
Reversed Hazard Rate ◽  
Generalized Gamma ◽  
Pareto Distributions ◽  
Hazard Rate Model

AbstractWe investigate stochastic comparisons of parallel systems (corresponding to the largest-order statistics) with respect to the reversed hazard rate and likelihood ratio orders for the proportional reversed hazard rate (PRHR) model. As applications of the main results, we obtain the equivalent characterizations of stochastic comparisons with respect to the reversed hazard rate and likelihood rate orders for the exponentiated generalized gamma and exponentiated Pareto distributions. Our results recover and strengthen some recent results in the literature.

scholarly journals Estimation of stress-strength reliability using record ranked set sampling scheme from the exponential distribution

Filomat ◽  
2015 ◽  
Vol 29 (5) ◽  
pp. 1149-1162 ◽  
Author(s):  
Mahdi Salehi ◽  
Jafar Ahmadi
Keyword(s):  
Maximum Likelihood ◽  
Exponential Distribution ◽  
Interval Estimation ◽  
Minimum Variance ◽  
Ranked Set Sampling ◽  
Strength Parameter ◽  
Likelihood Estimator ◽  
Data Set ◽  
Minimum Variance Unbiased Estimator ◽  
Upper Record

In this paper, point and interval estimation of stress-strength reliability based on upper record ranked set sampling (RRSS) from one-parameter exponential distribution are considered. Maximum likelihood estimator (MLE) as well as the uniformly minimum variance unbiased estimator (UMVUE) of stress-strength parameter are derived and their performance are studied. Also, some confidence intervals for stress-strength parameter based on upper RRSS are constructed and then compared on the basis of a simulation study. Finally, a data set has been analyzed for illustrative purposes.

Reconstruction of the past failure times for the proportional reversed hazard rate model

2012 ◽  
Vol 82 (3) ◽  
pp. 475-489 ◽  
Author(s):  
A. Asgharzadeh ◽  
Jafar Ahmadi ◽  
Z. Mirzazadeh Ganji ◽  
R. Valiollahi
Keyword(s):  
Hazard Rate ◽  
Rate Model ◽  
Reversed Hazard Rate ◽  
Failure Times ◽  
The Past ◽  
Hazard Rate Model

scholarly journals Ordering Awad–Varma Entropy and Applications to Some Stochastic Models

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 280
Author(s):  
Răzvan-Cornel Sfetcu ◽  
Sorina-Cezarina Sfetcu ◽  
Vasile Preda
Keyword(s):  
Shannon Entropy ◽  
Stochastic Models ◽  
Hazard Rate ◽  
Stochastic Order ◽  
Record Values ◽  
Residual Entropy ◽  
Proportional Hazard ◽  
Rate Model ◽  
Reversed Hazard Rate ◽  
Hazard Rate Model

We consider a generalization of Awad–Shannon entropy, namely Awad–Varma entropy, introduce a stochastic order on Awad–Varma residual entropy and study some properties of this order, like closure, reversed closure and preservation in some stochastic models (the proportional hazard rate model, the proportional reversed hazard rate model, the proportional odds model and the record values model).

scholarly journals Further Results on Dynamic Additive Hazard Rate Model

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Zhengcheng Zhang ◽  
Limin Zhang
Keyword(s):  
Hazard Rate ◽  
Stochastic Orders ◽  
Rate Model ◽  
Stochastic Comparisons ◽  
Reversed Hazard Rate ◽  
The Past ◽  
Hazard Rate Model ◽  
Aging Properties ◽  
Hazard Rate Models

In the past, the proportional and additive hazard rate models have been investigated in the works. Nanda and Das (2011) introduced and studied the dynamic proportional (reversed) hazard rate model. In this paper we study the dynamic additive hazard rate model, and investigate its aging properties for different aging classes. The closure of the model under some stochastic orders has also been investigated. Some examples are also given to illustrate different aging properties and stochastic comparisons of the model.

scholarly journals On Estimation of Reliability Functions using Record values from Proportional Hazard Rate Model

2019 ◽  
Vol 48 (3) ◽  
pp. 35-53
Author(s):  
Ajit Chaturvedi ◽  
Ananya Malhotra
Keyword(s):  
Hazard Rate ◽  
Real Data ◽  
Record Values ◽  
Minimum Variance ◽  
Proportional Hazard ◽  
Rate Model ◽  
Testing Procedures ◽  
Hazard Rate Model ◽  
Exact Confidence Intervals ◽  
Two Measures

Two measures of reliability functions, namely R(t)=P(X>t) and P=P(X<Y) have been studied based on record values from proportional hazard rate model (PHR) model. For estimation of P, we generalize the results of Basirat et al. (2016) when X and Y belong to different family of distributions from PHR model. Uniformly minimum variance unbiased estimator (UMVUE), maximum likelihood estimator (MLE) and Bayes estimator (BS) are obtained for the powers of the parameter and reliability functions. Simulation studies and a real data example have been presented for illustrative purposes. Asymptotic and exact confidence intervals of the parameters and reliability functions are constructed. Testing procedures are also developed for various hypotheses.

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