About: Grace Wahba

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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.

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rdfs:label	Grace Wahba (en) Grace Wahba (es) Grace Wahba (fr) Grace Wahba (it) Grace Wahba (pl)
rdfs:comment	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. (en) Grace Wahba (née le 3 août 1934) est une statisticienne américaine, titulaire de la chaire I. J. Schoenberg-Hilldale de professeur de statistiques à l'université du Wisconsin à Madison. (fr) Grace Wahba (3 agosto 1934) è una statistica statunitense.Autrice di contributi seminali nella teoria di lisciamento di dati soggetti a rumore, che trovano applicazioni in diversi settori di matematica applicata, ha sviluppato la convalida incrociata generalizzata e ha definito il problema di Wahba. (it) Grace Wahba (ur. 3 sierpnia 1934 w Montclair) – amerykańska matematyczka i statystyczka, emerytowany (od 2018) profesor statystyki Uniwersytetu Wisconsin w Madison. Jest pionierką technik wygładzania danych o dużej wariancji przy pomocy funkcji sklejanych. Najbardziej znana w związku z rozwojem metod uogólnionego sprawdzianu krzyżowego, oraz opisaniem związanego m.in. ze sterowaniem lotu sztucznych satelitów. Zapisała się także wkładem w stosowane metody demografii, uczenia maszynowego, analizy mikromacierzy DNA, finansów, obrazowania medycznego, i numerycznego modelowania klimatu. (pl) Grace Wahba (Estados Unidos, 3 de agosto de 1934) es una doctora en ciencias, pionera en los estudios de splines suavizados. Su libro sobre estos estudios, un clásico en la materia, fue la base de la investigación sobre el uso de splines y de las propuestas de nuevos estimadores con sus parámetros de suavizado asociados. Grace es conocida, sobre todo, por el desarrollo del método generalizado de validación cruzada para la selección del parámetro suavizado, método que se encuentra implementado en los paquetes estadísticos habituales. Sus aportaciones se enmarcan en el análisis de propiedades estadísticas de nuevos estimadores, así como en sus aplicaciones prácticas, aplicaciones de sus técnicas a estudios demográficos, microanálisis de ADN, estudio de imágenes médicas, cambio climático, mac (es)
foaf:name	Grace Wahba (en)
foaf:homepage	http://www.stat.wisc.edu/~wahba/
name	Grace Wahba (en)
foaf:depiction
birth date	1934-08-03 (xsd:date)
dcterms:subject	Living people 1934 births 20th-century American mathematicians 20th-century American women scientists 21st-century American women scientists American statisticians Cornell University alumni Fellows of the American Academy of Arts and Sciences Fellows of the American Association for the Advancement of Science Fellows of the American Statistical Association Fellows of the Institute of Mathematical Statistics Fellows of the Society for Industrial and Applied Mathematics Members of the United States National Academy of Sciences Stanford University alumni University of Maryland, College Park alumni University of Wisconsin–Madison faculty American women statisticians Machine learning researchers 20th-century women mathematicians 21st-century women mathematicians Bayesian statisticians dbc:21st-century__American_mathematicians
Wikipage page ID	7187724 (xsd:integer)
Wikipage revision ID	1118767772 (xsd:integer)
Link from a Wikipage to another Wikipage	American Statistical Association Numerical weather prediction Wing Hung Wong Demography University of Maryland, College Park University of Wisconsin–Madison Institute of Mathematical Statistics Living people Cornell University Mathematics Medical imaging Emanuel Parzen Gottfried E. Noether Cross-validation (statistics) Machine Learning Machine learning Madison, Wisconsin

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