Robust inference for one‐shot device testing data under exponential lifetime model with multiple stresses
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Introduced robust density‐based estimators in the context of one‐shot devices with exponential lifetimes under a single stress factor. However, it is usual to have several stress factors in industrial experiments involving one‐shot devices. In this paper, the weighted minimum density power divergence estimators (WMDPDEs) are developed as a natural extension of the classical maximum likelihood estimators (MLEs) for one‐shot device testing data under exponential lifetime model with multiple stresses. Based on these estimators, Wald‐type test statistics are also developed. Through a simulation study, it is shown that some WMDPDEs have a better performance than the MLE in relation to robustness. Two examples with multiple stresses show the usefulness of the model and, in particular, of the proposed estimators, both in engineering and medicine.
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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 | 0.000 | 0.009 |
| 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