When Signal-Guided Retention Loses to Index Coverage: A Character-Profile Budget Study
Abstract
A heuristic that directs observations toward changing signals can overlook variation hidden between similar endpoints. We tested such a retention rule on 2,858 released character-velocity profiles, comparing it with repeated splitting of the largest index gap. Both rules retained exactly sixteen or thirty-two observations and used linear reconstruction. Signal-guided retention increased mean profile error by 0.040904 at sixteen points and 0.005159 at thirty-two; character-clustered intervals were 0.015162-0.066646 and 0.000529-0.009790. Doubling the budget lowered pooled error under both rules. These results concern compression of already processed profiles from one writer, and do not evaluate real-time tablet sampling, character readability, or an image-restoration network.
Deterministic retention and reconstruction of public preprocessed pen-velocity profiles from one writer.
Original publication: October 31, 2026.
References
- Wasserstein, Ronald L.; Lazar, Nicole A.. (2016). The ASA Statement on p -Values: Context, Process, and Purpose. The American Statistician. https://doi.org/10.1080/00031305.2016.1154108.
- Suvorov, Roman; Logacheva, Elizaveta; Mashikhin, Anton; Remizova, Anastasia; Ashukha, Arsenii; Silvestrov, Aleksei; Kong, Naejin; Goka, Harshith; Park, Kiwoong; Lempitsky, Victor. (2021). Resolution-robust Large Mask Inpainting with Fourier Convolutions. arXiv:2109.07161. https://arxiv.org/abs/2109.07161.
- Carroll, Raymond J., David Ruppert, Leonard A. Stefanski, and Ciprian M. Crainiceanu. “Measurement Error in Nonlinear Models.” 2006. https://doi.org/10.1201/9781420010138.
- Little, Roderick J. A., and Donald B. Rubin. Statistical Analysis with Missing Data. Wiley, 2002. https://doi.org/10.1002/9781119013563.
- Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; Axton, Myles; Baak, Arie; Blomberg, Niklas; Boiten, Jan-Willem; da Silva Santos, Luiz Bonino; Bourne, Philip E.; Bouwman, Jildau; Brookes, Anthony J.; Clark, Tim; Crosas, Mercè; Dillo, Ingrid; Dumon, Olivier; Edmunds, Scott; Evelo, Chris T.; Finkers, Richard; Gonzalez-Beltran, Alejandra; Gray, Alasdair J.G.; Groth, Paul; Goble, Carole; Grethe, Jeffrey S.; Heringa, Jaap; ’t Hoen, Peter A.C; Hooft, Rob; Kuhn, Tobias; Kok, Ruben; Kok, Joost; Lusher, Scott J.; Martone, Maryann E.; Mons, Albert; Packer, Abel L.; Persson, Bengt; Rocca-Serra, Philippe; Roos, Marco; van Schaik, Rene; Sansone, Susanna-Assunta; Schultes, Erik; Sengstag, Thierry; Slater, Ted; Strawn, George; Swertz, Morris A.; Thompson, Mark; van der Lei, Johan; van Mulligen, Erik; Velterop, Jan; Waagmeester, Andra; Wittenburg, Peter; Wolstencroft, Katherine; Zhao, Jun; Mons, Barend. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. https://doi.org/10.1038/sdata.2016.18.
- Gebru, Timnit, et al. "Datasheets for datasets" Communications of the ACM, 2021. https://doi.org/10.1145/3458723.
- Bland, J. Martin, and Douglas G. Altman. "Statistical Methods for Assessing Agreement between Two Methods of Clinical Measurement." The Lancet, vol. 327, no. 8476, 1986, pp. 307-310. https://doi.org/10.1016/S0140-6736(86)90837-8.
- Lin, Lawrence I-Kuei. (1989). A Concordance Correlation Coefficient to Evaluate Reproducibility. Biometrics. https://doi.org/10.2307/2532051.
- Keogh, Eamonn; Chakrabarti, Kaushik; Pazzani, Michael; Mehrotra, Sharad. (2001b). Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases. Knowledge and Information Systems. https://doi.org/10.1007/pl00011669.
- de Boor, Carl. (1978). A Practical Guide to Splines. Applied Mathematical Sciences. https://doi.org/10.1007/978-1-4612-6333-3.
- Meng, Zijie; Zeng, Yuanze; Chang, Xiang; Xu, Tianshuo; Chao, Fei; Cao, Xixin; Shang, Changjing; Shen, Qiang. (2025). Orpaint: a zero-shot inpainting model for oracle bone inscription rubbings with visual mamba block. Science China Information Sciences, 68(8), 189102. https://doi.org/10.1007/s11432-024-4493-4.
- Keogh, E.; Chu, S.; Hart, D.; Pazzani, M.. (2001a). An online algorithm for segmenting time series. Proceedings 2001 IEEE International Conference on Data Mining. https://doi.org/10.1109/icdm.2001.989531.
- White, Halbert. “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica, vol. 48, no. 4, 1980, pp. 817–838. https://doi.org/10.2307/1912934.
- Ramer, Urs. (1972). An iterative procedure for the polygonal approximation of plane curves. Computer Graphics and Image Processing. https://doi.org/10.1016/s0146-664x(72)80017-0.
- Cameron, A. Colin, and Douglas L. Miller. “A Practitioner’s Guide to Cluster-Robust Inference.” Journal of Human Resources, vol. 50, no. 2, 2015, pp. 317–372. https://doi.org/10.3368/jhr.50.2.317.
- Fritsch, F. N.; Carlson, R. E.. (1980). Monotone Piecewise Cubic Interpolation. SIAM Journal on Numerical Analysis. https://doi.org/10.1137/0717021.
- Ioannidis, John P. A.. (2005). Why Most Published Research Findings Are False. PLoS Medicine. https://doi.org/10.1371/journal.pmed.0020124.
- Liu, Guilin; Reda, Fitsum A.; Shih, Kevin J.; Wang, Ting-Chun; Tao, Andrew; Catanzaro, Bryan. (2018). Image Inpainting for Irregular Holes Using Partial Convolutions. arXiv:1804.07723. https://arxiv.org/abs/1804.07723.
- Shuman, David I; Narang, Sunil K.; Frossard, Pascal; Ortega, Antonio; Vandergheynst, Pierre. (2012). The Emerging Field of Signal Processing on Graphs: Extending High-Dimensional Data Analysis to Networks and Other Irregular Domains. arXiv:1211.0053. https://arxiv.org/abs/1211.0053.
- Cook, R. Dennis. (1977). Detection of Influential Observation in Linear Regression. Technometrics. https://doi.org/10.1080/00401706.1977.10489493.
- DOUGLAS, DAVID H; PEUCKER, THOMAS K. (1973). ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE. Cartographica. https://doi.org/10.3138/fm57-6770-u75u-7727.
- Ulyanov, Dmitry; Vedaldi, Andrea; Lempitsky, Victor. (2017). Deep Image Prior. arXiv:1711.10925. https://arxiv.org/abs/1711.10925.
- Lake, Brenden M.; Salakhutdinov, Ruslan; Tenenbaum, Joshua B.. (2019). The Omniglot challenge: a 3-year progress report. https://arxiv.org/abs/1902.03477.
- Alpaydin, E.; Alimoglu, Fevzi. (1996). Pen-Based Recognition of Handwritten Digits [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5MG6K.
- Ortega, Antonio; Frossard, Pascal; Kovačević, Jelena; Moura, José M. F.; Vandergheynst, Pierre. (2017). Graph Signal Processing: Overview, Challenges and Applications. arXiv:1712.00468. https://arxiv.org/abs/1712.00468.
- Wang, Mei; Deng, Weihong. (2024). A dataset of oracle characters for benchmarking machine learning algorithms. Scientific Data, 11, 87. https://doi.org/10.1038/s41597-024-02933-w.
- Williams, Ben. (2006). Character Trajectories [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C58G7V.
- Koo, Terry K., and Mae Y. Li. "A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research." Journal of Chiropractic Medicine, vol. 15, no. 2, 2016, pp. 155-163. https://doi.org/10.1016/j.jcm.2016.02.012.
- Pathak, Deepak; Krahenbuhl, Philipp; Donahue, Jeff; Darrell, Trevor; Efros, Alexei A.. (2016). Context Encoders: Feature Learning by Inpainting. arXiv:1604.07379. https://arxiv.org/abs/1604.07379.
- Lugmayr, Andreas; Danelljan, Martin; Romero, Andres; Yu, Fisher; Timofte, Radu; Van Gool, Luc. (2022). RePaint: Inpainting using Denoising Diffusion Probabilistic Models. arXiv:2201.09865. https://arxiv.org/abs/2201.09865.
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