|Born||August 3, 1934|
University of Maryland, College Park
|Known for||generalized cross validation, smoothing splines|
|Fields||Mathematics, Statistics, Machine Learning|
|Institutions||University of Wisconsin–Madison|
|Thesis||Cross Spectral Distribution Theory for Mixed Spectra and Estimation of Prediction Filter Coefficients|
|Doctoral advisor||Emanuel Parzen|
Grace Goldsmith Wahba (born August 3, 1934) is an American statistician and now-retired I. J. Schoenberg-Hilldale Professor of Statistics at the University of Wisconsin–Madison. She is a pioneer in methods for smoothing noisy data. Best known for the development of generalized cross-validation and "Wahba's problem", she has developed methods with applications in demographic studies, machine learning, DNA microarrays, risk modeling, medical imaging, and climate prediction.
Biography [ edit ]
Wahba studied at Cornell University for her undergraduate degree. When she was there women were severely restricted in their privileges, for example she was required to live in a dorm and had a curfew. She received her bachelor's degree in 1956 and a master's degree from the University of Maryland, College Park in 1962. She worked in industry for several years before receiving her doctorate from Stanford University in 1966 and settling in Madison in 1967.
Honors and awards [ edit ]
Wahba is a member of the National Academy of Sciences, and a fellow of several academic societies including the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics. Over the years she has received a selection of notable awards in the statistics community:
- R. A. Fisher Lectureship, COPSS, August 2014
- Gottfried E. Noether Senior Researcher Award, Joint Statistics Meetings, August 2009
- Committee of Presidents of Statistical Societies Elizabeth Scott Award, 1996
- First Emanuel and Carol Parzen Prize for Statistical Innovation, 1994
References [ edit ]
- "Breaking ground with Grace". news.wisc.edu. Retrieved 2018-11-16.
- Craven, Peter; Wahba, Grace (1978-12-01). "Smoothing noisy data with spline functions". Numerische Mathematik. 31 (4): 377–403. doi:10.1007/BF01404567. ISSN 0945-3245.
- "Grace Goldsmith Wahba | Department of Statistics". statistics.stanford.edu. Retrieved 2019-10-06.
- Wahba, G. (1990-01-01). Spline Models for Observational Data. CBMS-NSF Regional Conference Series in Applied Mathematics. Society for Industrial and Applied Mathematics. doi:10.1137/1.9781611970128. ISBN 9780898712445.
- "National Academy of Sciences". National Academy of Sciences. Retrieved 22 February 2016.
- "Graca Wahba: Honors". Grace Wahba: Honors. Retrieved 22 February 2016.
- "Institute of Mathematical Statistics". Institute of Mathematical Statistics. Archived from the original on 12 March 2016. Retrieved 22 February 2016.