The data consists of multivariate failure times under right random censorship. By the kernel smoothing technique, convolutions of cumulative multivariate hazard functions suggest estimators of the so-called multivariate hazard functions. We establish strong i.i.d. representations and uniform bounds
Multivariate hazard rate orders
โ Scribed by Taizhong Hu; Baha-Eldin Khaledi; Moshe Shaked
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 232 KB
- Volume
- 84
- Category
- Article
- ISSN
- 0047-259X
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
It is well known that the hazard rate of a univariate normal distribution is increasing. In this paper, we prove that the hazard gradient, in the case of general multivariate normal distribution, is increasing in the sense of Johnson and Kotz. 1997 Academic Press 1. Definition 1. The joint multivar
For the multivariate log-concave distribution, it is shown that the hazard gradient is increasing in the sense of Johnson and Kotz. As an immediate consequence, the result of Gupta and Gupta (1997) on the multivariate normal hazard is obtained.