|Alma mater||University of Toronto|
Penn State University
|Thesis||Smoothing Data with Correlated Errors (1988)|
|Academic advisors||Iain M. Johnstone|
Naomi Altman is a statistician known for her work on kernel smoothing[KS] and kernel regression,[KR] and interested in applications of statistics to gene expression and genomics. She is a professor of statistics at Pennsylvania State University, and a regular columnist for the "Points of Significance" column in Nature Methods.
Education and career
Altman studied mathematics at the University of Toronto, graduating in 1974, and spent two years teaching at Government Teacher's Training College in Lafia, Nigeria. Returning to Canada, she earned a master's degree in statistics from Toronto in 1979.
After working as a statistical consultant at Simon Fraser University and the University of British Columbia. She completed her doctorate in 1988 from Stanford University. Her dissertation, supervised by Iain M. Johnstone, was Smoothing Data with Correlated Errors.
Altman and her coauthor Julio C. Villarreal won the 2005 Canadian Journal of Statistics Award for their paper "Self-modelling regression for longitudinal data with time-invariant covariates".[AV] In 2009, Altman became a Fellow of the American Statistical Association.
- Curriculum vitae (PDF), 2016, retrieved 2017-11-17
- "Points of Significance", Nature Methods, retrieved 2017-11-17
- Naomi Altman at the Mathematics Genealogy Project
- Naomi S. Altman and Julio C. Villarreal, The Canadian Journal of Statistics Award 2005, Statistical Society of Canada, retrieved 2017-11-17
- ASA Fellows list, American Statistical Association, archived from the original on 2017-12-01, retrieved 2017-11-17