Name
Abstract | ||
|---|---|---|
The study presents the estimation of the location of the change in the hazard-rate function of the survival times of patients who continue to live after a major life-threatening medical operation. The real data set that acts as a backbone for the present work is the Stanford heart transplantation data. On studying and interpreting, the non-parametric hazard rate plot, and cumulative hazard curve of the data, a suitable hazard rate model is proposed. The parameters involved in the proposed model have been assessed by the classical and Bayesian methods estimation. The likelihood-ratio test has been conducted to test the validity of the change time point in the data. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s13198-021-01601-1 | International Journal of System Assurance Engineering and Management |
Keywords | DocType | Volume |
Change-time hazard-rate model, Cumulative hazard function, Survival function, Metropolis-Hasting algorithm, Gibbs sample | Journal | 13 |
Issue | ISSN | Citations |
4 | 0975-6809 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bhupendra Singh | 1 | 35 | 5.44 |
| Shubhi Rathi | 2 | 0 | 0.34 |
| Gajraj Singh | 3 | 0 | 0.34 |
| Puneet Kumar Gupta | 4 | 0 | 0.34 |