Comparison of two sampling schemes for generating record-breaking data from the proportional hazard rate models

2015 ◽  
Vol 45 (13) ◽  
pp. 3721-3733 ◽  
Author(s):  
Mahdi Salehi ◽  
Jafar Ahmadi ◽  
Sanku Dey
Keyword(s):  
Hazard Rate ◽  
Proportional Hazard ◽  
Sampling Schemes ◽  
Hazard Rate Models

scholarly journals Results on Varextropy Measure of Random Variables

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 356
Author(s):  
Nastaran Marzban Vaselabadi ◽  
Saeid Tahmasebi ◽  
Mohammad Reza Kazemi ◽  
Francesco Buono
Keyword(s):  
Hazard Rate ◽  
Random Variables ◽  
Record Values ◽  
Comparison Method ◽  
Dispersion Measure ◽  
Stochastic Comparison ◽  
Alternative Measure ◽  
Proportional Hazard ◽  
Hazard Rate Models ◽  
Measure Of Uncertainty

In 2015, Lad, Sanfilippo and Agrò proposed an alternative measure of uncertainty dual to the entropy known as extropy. This paper provides some results on a dispersion measure of extropy of random variables which is called varextropy and studies several properties of this concept. Especially, the varextropy measure of residual and past lifetimes, order statistics, record values and proportional hazard rate models are discussed. Moreover, the conditional varextropy is considered and some properties of this measure are studied. Finally, a new stochastic comparison method, named varextropy ordering, is introduced and some of its properties are presented.

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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