APPLIED REGRESSION ANALYSIS BIBLIOGRAPHY UPDATE 2000–2001
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 25-page Bibliography in Applied Regression Analysis, 2nd edition, by N.R. Draper and H. Smith, published by John Wiley and Sons in 1981, was previously extended by these publications: 1. Applied Regression Analysis Bibliography Update 1988-89. Communications in Statistics, Theory and Methods 1990, 19(4), 1205 1229. 2. Applied Regression Analysis Bibliography Update 1990-91. Communications in Statistics. Theory and Methods 1992, 21(9), 2415-2437. 3. Applied Regression Analysis Bibliography Update 1992-93. Commuications in Statistics. Theory and Methods 1994, 23(9), 2701-2731. The subheadings in 1-3 match the chapter headings of the 2nd Edition. The subheadings of 4 and 5 below, and of the present Bibliography for 2000-2001, are reclassified to match the chapter headings of Applied Regression Analysis, 3rd Edition, published by John Wiley and Sons, in 1998. 4. Applied Regression Analysis Bibliography Update 1994-97. Communications in Statistics. Theory and Methods 1998, 27(10), 2581-2623. 5. Applied Regression Analysis Bibliography Update 1998-99. Communications in Statistics. Theory and Methods 2000, 29(9&10), 2313-2341. 6. This Bibliography for 2000-2001. Items were chosen on the basis of their perceived relevance to practical applications (sometimes rather widely interpreted). The references were selected mostly from the issues of these journals: Annals of Statistics; Biometrika; Bulletin of the International Statistical Institute; Canadian Journal of Statistics; Communications in Statistics--Simulation and Computation; Communications in Statistics-Theory and Methods; Journal of the American Statistical Association; Journal of Quality Technology; Journal of the Royal Statistical Society, Series A, B, C and D; and Technometrics. This will be the last of these updates to be published in Communications in Statistics and I am grateful to the Editors for their long-lasting courtesy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.001 | 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