statistics faculty at unc-ch
(Who was Amos Hawley?)
Go here to see some novel data analyses (by smoothing, SiZer, and other methods).
Go here to see some movies (about smoothing and more).
Go here to see a list of downloadable preprints.
for downloadable transparencies from talks.
Acknowledgement of support: much of the
in the above pages was supported by NSF Grants
DMS-0308331, DMS-0606577 and also many other
grants with a wide range
XploRe (statistical computing environment produced by Wolfgang Haerdle and MDTech).
Objects (XLispStat macros written by
SiZer in R, (by Derek Sonderegger)
- Department of Statistics (1982 - 2003)
- Department of Statistics and Operations Research (2003 - )
- Adjunct Professor in Computer Science (2003 - )
- Member, Lineberger Cancer Center (2004 - )
- Department of Biostatistics (2007 - )
Marron's previous theoretical interests were in smoothing methods for curve estimation. These give a flexible and powerful approach to data analysis, especially useful in situations where a good parametric model is unknown, or there is a need for visual model checking. Mathematical analysis, especially a wide array of asymptotics, to the depth of minimax lower bounds, is a frequently used methodological research tool in this area. However computational, numerical and graphical methods are also indispensable. These techniques are broadly applicable in most areas of science where numbers and uncertainty are involved. Personal application areas include biology, economics, geology, human movement, image analysis, marketing, ophthalmology and software engineering.
“Visualizing the Structure of
Aydin, B., Pataki, G., Wang, H., Ladha, A.,
Bullitt, E. Marron, J. S.
(2011) Electronic Journal of
“Principal Arc Analysis on
manifolds”, S. Jung, M. Foskey and J. S. Marron
Annals of Applied Statistics, 5, 578-603.
“Asymptotic Properties of
Discrimination”, Qiao, X., Zhang, H. H., Liu,
Y., Todd, M. J. and
Marron, J. S.
(2010) Journal of the American
Association, 105, 401–414.
“PCA Consistency in High Dimension, Low Sample Size Context”, Jung, S. and Marron, J. S., (2009), Annals of Statistics, 37, 4104-4130.
A brief survey of bandwidth selection for density estimation (with M. C. Jones and S. J. Sheather), Journal of the American Statistical Association, 91 (1996), 401-407.