Estimating functional single index models with compact support
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The functional single index models are widely used to describe the nonlinear relationship between a scalar response and a functional predictor. The conventional functional single index model assumes that the coefficient function is nonzero in the entire time domain. In other words, the functional predictor always has a nonzero effect on the response all the time. We propose a new compact functional single index model, in which the coefficient function is only nonzero in a subregion. We also propose an efficient method that can simultaneously estimate the nonlinear link function, the coefficient function and also the nonzero region of the coefficient function. Hence, our method can identify the region in which the functional predictor is related to the response. Our method is illustrated by an application example in which the total number of daily bike rentals is predicted based on hourly temperature data. The finite sample performance of the proposed method is investigated by comparing it to the conventional functional single index model in a simulation study
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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 | 0.000 |
| 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) | 0.006 | 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