statistics faculty at unc-ch
______________
marron@email.unc.edu
309 Smith
919-962-2188
Fax:
919 962-1279
-
J.
S. Marron
(Steve Marron)
-
Amos Hawley
Distinguished Professor
(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.
Go here
for downloadable transparencies from talks.
Acknowledgement of support: much of the
research presented
in the above pages was supported by NSF Grants DMS-8902973,
DMS-9203135,
DMS-9504414, DMS-9971649,
DMS-0308331, DMS-0606577 and also many other grants with a wide range
of collaborators.
Recommended Links
XploRe (statistical computing environment produced by Wolfgang Haerdle and MDTech).
KDE
Objects (XLispStat macros written by Frederic Udina).
Distance Weighted
Discrimination, for removing biases in microarray data (supported
by caBIG)
SiZer in R, (by Derek Sonderegger)
Education
B.S. (1977),
University of California,
Davis;
Ph.D. (1982), University
of California, Los Angeles.
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UNC-Chapel Hill (1982
- ):
- 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 - )
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Fellow - Institute of
Mathematical Statistics; Fellow - American Statistical Association,
Elected Member -
International Statistical Institute, #15 on ISI List of Most Highly
Cited Mathematicians - 1991-2001, Amos H. Hawley Distinguished Professor - University of
North Carolina, S. N. Roy Memorial Lecturer - University of Calcutta.
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Research Interests
-
Marron's current
interests are in the area of analyzing data that lie in non-standard
spaces. The contexts include High Dimension Low Sample Size
(HDLSS) data, and/or data exotic data types, such as manifold and
tree-structured data. An overarching framework for this research is Object Oriented Data Analysis
(OODA). This work is motivated by collaborations in cancer
research, genetics, image analysis, evolutionary biology, drug
discovery and toxicology. It has spawned a new branch of
mathematical statistics: HDLSS asymptotics, where the limiting
operation has the dimension growing while the sample size is fixed.
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.
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(Go here
to see a complete list)
Improved variable window estimators of probability densities (with P. Hall and T. C. Hu), Annals of Statistics, 23 (1995), 1-10.
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.
Bootstrap selection of the smoothing parameter in nonparametric hazard rate estimation (with W. Gonzlez-Manteiga and R. Cao), Journal of the American Statistical Association, 91 (1996), 1130-1140.
