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Spline Models for Observational Data
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“As shown in [18], Equation (1) can be analytically solved efficiently; details are provided in Appendix 9.1.”
From Learning from Demonstrations Through the Use of Non-rigid Registration (2016) · cites this paper as [18]
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Chen, M., Jiang, H., Liao, W., & Zhao, T. (2022) · Information and Inference A Journal of the IMA · doi:10.1093/imaiai/iaac001 · Cited by 81
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Wang, F., & Sun, J. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2425365 · Cited by 51
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Plate, T. A. (1999) · Behaviormetrika · doi:10.2333/bhmk.26.29 · Cited by 49
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Ching, K., Rau, R., & Zeng, Y. (2007) · Journal of Geophysical Research Atmospheres · doi:10.1029/2006jb004439 · Cited by 49
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Liew, A. W., Yan, H., & Law, N.-F. (2005) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2005.848303 · Cited by 49
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Yee, P., & Haykin, S. (1999) · IEEE Transactions on Signal Processing · doi:10.1109/78.782193 · Cited by 48
Perez, J. D., Kozlowski, G., Brandt, P. C., et al. (2001) · Geophysical Research Letters · doi:10.1029/2000gl012636 · Cited by 48
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Cen, S., Gebregziabher, M., Moazami, S., Azevedo, C. J., & Pelletier, D. (2023) · Scientific Reports · doi:10.1038/s41598-023-43618-5 · Cited by 55
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She, B., Wang, Y., Liang, J., et al. (2018) · Geophysics · doi:10.1190/geo2017-0615.1 · Cited by 46
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Lukas, M. A. (2008) · Inverse Problems · doi:10.1088/0266-5611/24/3/034006 · Cited by 46
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McMillan, N. J., Sacks, J., Welch, W. J., et al. (1999) · Journal of Biopharmaceutical Statistics · doi:10.1081/bip-100101005 · Cited by 46
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Lin, Y., Wahba, G., Zhang, H., & Lee, Y. (2002) · Machine Learning · doi:10.1023/a:1013951620650 · Cited by 46
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Davis, K., & Li, Y. (2013) · Geophysics · doi:10.1190/geo2012-0192.1 · Cited by 46
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Metadata
- Authors
- Wahba, G.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Wahba, Grace
- Venue
- Society for Industrial and Applied Mathematics eBooks
- Published
- 1990-01-01
- OpenAlex
- W4298876635
- Cited by
- 4,184
- References
- 0
- Citations by year
- 2026: 89 · 2025: 147 · 2024: 135 · 2023: 141 · 2022: 156 · 2021: 191 · 2020: 184 · 2019: 154 · 2018: 165 · 2017: 156 · 2016: 140 · 2015: 152 · 2014: 156 · 2013: 161 · 2012: 163
- FWCI
- 17.89
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Society for Industrial and Applied Mathematics eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Keywords
- spline models, smoothing splines, nonparametric regression, penalized splines, bandwidth selection, loess
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