|
statistics faculty at unc-ch _____________ 311
New West |
Edward Carlstein Professor
and Chairman
Education B.Sc.
(1979), Cornell University; M.A. (1980), M.Phil. (1983), Ph.D. (1984), Yale
University. Honors and Awards 1997
recipient of the Tanner Award for Excellence in Undergraduate Teaching Faculty Positions UNC-Chapel
Hill (1984- ). Research Interests Carlstein's
main research interests are in methods of nonparametric statistical
inference, that is, methods which do not require the user to know what
particular distribution or model produced the data at hand. Such methods are
needed when the statistician lacks prior knowledge of the underlying
data-generating process, or when the statistician wants a robust corroborator
for results from a parametric analysis of the data. He is especially
interested in nonparametric estimation of change-points and boundaries, and
of sampling distributions (via resampling). A change-point is the time at
which observations in a sequence cease to arise from the "old"
distribution and begin to arise from a "new" distribution;
nonparametric estimation of change-points is important in quality control and
in epidemiology. When observations are on a grid, as in image-analysis or
geological data, a boundary may partition the observations into homogeneous
groups; this boundary can be estimated nonparametrically using methods
analogous to the change-point estimators.In order to make statistical
inferences, one needs information about the sampling distribution of the
statistic at hand. Although in many situations the sampling distribution is
known to be approximately normal, there are many other cases where the
sampling distribution cannot be derived theoretically, and may be quite
non-normal, for example if the statistic is extremely complicated or if the
observations are not independent. Resampling methods, such as the jackknife
and the bootstrap, allow the statistician to nonparametrically estimate
sampling distributions in these difficult situations, essentially by re-using
the observed data. Selected Publications Boundary
estimation (with C. Krishnamoorthy), Journal of the American Statistical
Association, 87 (1992), 430-438. Nonparametric
estimation of the moments of a general statistic computed from spatial data
(with M. Sherman), Journal of the American Statistical Association, 89
(1994), 496-500. Nonparametric
change-point estimation for data from an ergodic sequence (with S. Lele), Theory
of Probability and its Applications, 38 (1994), 726-733. Replicate
histograms (with M. Sherman), Journal of the American Statistical
Association, 91 (1996), 566-576. Matched-block
bootstrap for dependent data (with K. Do, P. Hall, T. Hesterberg, H. Kunsch),
Bernoulli (1997). |
