Naomi Altman | |
---|---|
Citizenship | United States |
Alma mater |
University of Toronto Stanford University |
Scientific career | |
Institutions |
Cornell University Penn State University |
Academic background | |
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, [1] and a regular columnist for the "Points of Significance" column in Nature Methods. [2]
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. [1]
After working as a statistical consultant at Simon Fraser University and the University of British Columbia, she completed her doctorate in 1988 at Stanford University. [1] Her dissertation, supervised by Iain M. Johnstone, was Smoothing Data with Correlated Errors. [1] [3]
She joined the Cornell University faculty, in the Biometrics Unit, and became chair of the Department of Biometrics there from 1997 to 2000. She moved to Penn State in 2001. [1]
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". [4] [AV] In 2009, Altman became a Fellow of the American Statistical Association. [5]
KS. | Altman, N. S. (September 1990),
"Kernel smoothing of data with correlated errors", Journal of the American Statistical Association, 85 (411): 749–759,
doi:
10.1080/01621459.1990.10474936,
hdl:
1813/33092,
JSTOR
2290011
|
KR. | Altman, N. S. (August 1992),
"An introduction to kernel and nearest-neighbor nonparametric regression", The American Statistician, 46 (3): 175–185,
doi:
10.1080/00031305.1992.10475879,
hdl:
1813/31637,
JSTOR
2685209
|
AV. |