 Associate
Professor of Statistics- Ph.D., Iowa State University, 1990
Summary of research interests
Dr. Rathbun’s research focuses on the application
of geospatial statistical methods to ecology and the
environmental sciences. Emphasis is given to geostatistical
data and spatial point patterns.
Geostatistics involves data that may be collected at
any sample of locations in a region of interest. Such
data may include the concentrations of chemical contaminants
or counts of numbers of individual organisms or species.
Naïve approaches to handling left-censored data
can yield biased estimates of model parameters and biased
predictions at unsampled sites. Dr. Rathbun has developed
methods for geostatistical analysis of left-censored
spatial data. Applications include data from estuaries,
soil nemotodes, and the fresh water marshes of the Florida
Everglades. Current research considers multivariate
geostatistical methods for modeling the interactions
among multiple environmental variables.
The spatial point pattern formed by individual organisms
results from past patterns of birth, growth, and survivorship,
and so, the investigation of spatial point patterns
can lead to a better understanding of these important
demographic processes. Dr. Rathbun’s research
has focused on the methods for modeling the effects
of partially observed environmental variables on spatial
point patterns, and on the development of spatiotemporal
point process models. Applications include the spatial
point patterns of forest trees, turtle nests, and earthquakes.
Representative publications
Lin, H., and Rathbun, S.L. 2003. Hierarchical frameworks
for multiscale bridging in hydropedology. In Y. Pachepsky,
D. Radcliffe, and H.M. Selim (eds.), Scaling Methods
in Soil Physics, pp. 347-371. CRC Press, Boca Raton,
FL.
C. H. Ettema, S. L. Rathbun, and D. C. Coleman. 2000.
On spatiotemporal patchiness and the coexistence of
five species of Chronogaster (Nematoda:Chronogasteridae)
in a riparian wetland. Oecologia 125: 444-452.
S. L. Rathbun. 1998. Spatial modeling in irregularly
shaped regions: Kriging estuaries. Environmetrics
9: 109-130.
S. L. Rathbun. 1996. Asymptotic properties of the maximum
likelihood estimator for spatiotemporal point processes.
Journal of Statistical Planning and Inference
51: 55-74.
S. L. Rathbun. 1996. Estimation of Poisson intensity
using partially observed concomitant variables. Biometrics
52: 226-242.
S. L. Rathbun and N. Cressie. 1994. Space-time survival
point processes: longleaf pines in southern Georgia.
Journal of the American Statistical Association
89: 1164-1174.
Last updated: 28 February
2005
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