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 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.

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 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.

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).

Railway Passengers Travel Time Research Based on Survival Analysis

2014 ◽  
Vol 962-965 ◽  
pp. 2580-2583
Author(s):  
Ya Chen Zhao ◽  
Zhen Yu Zhang ◽  
Qing Jie Zheng
Keyword(s):  
Survival Analysis ◽  
Travel Time ◽  
Significant Influence ◽  
Hazard Rate ◽  
Family Income ◽  
Proportional Hazard ◽  
Rate Model ◽  
Analysis Method ◽  
Cox Proportional Hazard ◽  
Hazard Rate Model

With the development of the economy, people have higher request for the time. Studying the choice of travel about rail passengers becomes more significant. Due to these problem above and using survival analysis method, this paper builds travel time survival model based on questionnaire and have a whole analysis of the travel time of the rail passenger. Then, it concludes that most of the rail passengers’ travel time is below five hours. At last, this paper builds COX proportional hazard rate model of travel time and study the factors about travel time. The result demonstrates that the factor about whether it is students or not, family income, whether it is travelling and the number of packages has a significant influence on the travel time.

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