Parameter Estimation for the Linear Hazard Rate Distribution Based on Records and Inter-record Times
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Bibliographic record
Abstract
The linear hazard rate distribution (LHRD) is a two-parameter distribution that contains exponential and generalized Rayleigh distributions as special cases. It has applications in a number of fields including reliability improvement, life testing, and survival analysis. An iterative EM algorithm is presented to compute maximum likelihood estimates (MLEs) for the LHRD based on records and inter-record times. Simulation results indicate that the estimates obtained by maximum likelihood method are better than those obtained by the least-squares type estimation and by the elemental percentile method. We also evaluate the expected values and variances of the MLEs for various sample sizes in order to determine the unbiasing factors of the MLEs which can be utilized in performing tests of exponentiality and also for examining the appropriateness of Rayleigh model to data at hand.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it