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 |
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Pages (from-to) | 159-166 |
Number of pages | 8 |
Journal | Statistics |
Volume | 46 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Jan 2012 |
Keywords
- sequential order statistics
- conditional proportional hazard rates
- sequential k-out-of-n system
- regular exponential family
- maximum likelihood estimation
- uniformly minimum variance unbiased estimation
- Fisher information matrix
- asymptotic efficiency
- OF-N SYSTEMS
- DISTRIBUTIONS
- INFERENCE