L-moments of asymmetric generalized distributions obtained through quantile splicing
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Bibliographic record
Abstract
Balakrishnan et al. (Communications in Statistics Simulation and Computation 46 (2017) 4082–4097) proposed a skew logistic distribution by making use of the cumulative distribution function (CDF) of the folded logistic distribution. They made use of moments of order statistics from the standard folded logistic distribution to obtain the single and product moments of order statistics from the skew logistic distribution. Subsequently, Mac’Oduol et al. (Communications in Statistics—Theory and Methods 49 (2020) 4413–4429) proposed quantile splicing for the construction of two-piece distributions using quantile functions of symmetric distributions as building blocks. This paper presents the derivation of a general formula for the L-moments of such two-piece distributions. In addition, quantile splicing and its results are then specialized to the Tukey lambda distribution, and an example is used to illustrate the results developed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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