Reliability Analysis for Two Components Connected in Parallel with Lindley Probability Model
Bibliographic record
Abstract
Reliability of structures has been discussed by several authors using probability models. Some of the early researches have been discussed by Birnbaum (1956) [1] in which two independent variables X and Y are defined as “Strength” and “Stress” respectively. This research is an extension of Mann- Whitney paper (1947) [2] on P(Y<X). Beg (1979c, 1980b, 1980c) [3-5] estimated reliability i.e R = P(Y<X), by taking two parameter Pareto and Power function distributions. Gupta and Gupta (1990) [6] have found point estimates of R=P(aX> bY) by Maximum likelihood and MVUE of R. In the present paper we have considered R=P(Y<X) where X and Y independently follow Lindley distribution. The MLE and Moment estimators of the distribution and then that of R have been found. A simulation study has been done to estimate biasedness and Confidence interval of R.
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How this classification was reachedexpand
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 | 0.036 | 0.141 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".