Some aspects of robust estimation in time series analysis.
Why this work is in the frame
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Bibliographic record
Abstract
In this thesis, a number of robust methods have been developed for estimating the parameters in a time series setting. To estimate the power spectrum of an ARMA process, an M estimation method has been introduced which maximizes the robust likelihood function of the discrete Fourier transforms of the process. This robust method is useful in estimating the parameters of the continuous spectrum ARMA process by downweighting the influence of possible discrete spectrum harmonic components on the data. The proposed M estimation method has been applied to some actual time series data sets of sea level records, where a strong presence of tidal (harmonic) components is observed along with the continuous spectrum surge process. Here robust estimation of the power spectrum of the surge process has been considered assuming that the surge follows an ARMA process.
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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 | 0.000 |
| 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