Abstract
Generalized order statistics, and thus sequential order statistics with conditional proportional hazard rates, are shown to form a regular exponential family in the model parameters. This structure is utilized to derive maximum likelihood estimators for these parameters or functions of them along with several properties of the estimators. The Fisher information matrix is stated, and asymptotic efficiency is shown.
| Original language | English |
|---|---|
| Pages (from-to) | 159-166 |
| Number of pages | 8 |
| Journal | Statistics |
| Volume | 46 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Apr 2012 |
| Externally published | Yes |
Keywords
- asymptotic efficiency
- conditional proportional hazard rates
- Fisher information matrix
- maximum likelihood estimation
- regular exponential family
- sequential k-out-of-n system
- sequential order statistics
- uniformly minimum variance unbiased estimation