Empirical-Bayes Estimation of Mean Life for a Censored Sample, Constant Hazard Rate Model

1986 ◽  
Vol 35 (4) ◽  
pp. 399-402 ◽  
Author(s):  
Ashok Singh ◽  
Anita Singh
Keyword(s):  
Hazard Rate ◽  
Empirical Bayes ◽  
Bayes Estimation ◽  
Rate Model ◽  
Empirical Bayes Estimation ◽  
Hazard Rate Model ◽  
Censored Sample

Bayes estimation of the mixture of hazard-rate model

1997 ◽  
Vol 55 (1) ◽  
pp. 9-13 ◽  
Author(s):  
K.K. Sharma ◽  
Hare Krishna ◽  
Bhupendra Singh
Keyword(s):  
Hazard Rate ◽  
Bayes Estimation ◽  
Rate Model ◽  
Hazard Rate Model

Bayes estimation of the linear hazard-rate model

1993 ◽  
Vol 42 (4) ◽  
pp. 636-640 ◽  
Author(s):  
A. Pandey ◽  
A. Singh ◽  
W.J. Zimmer
Keyword(s):  
Hazard Rate ◽  
Bayes Estimation ◽  
Rate Model ◽  
Hazard Rate 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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