Upcoming Appearances
American University; Washington, DC
June 6, 2019
Princeton University; Princeton, NJ
June 19-21, 2019
Los Alamos, New Mexico
August 7, 2019
Kuala Lumpur, Malaysia
August 18-23, 2019
Grand Rapids, Michigan
October 10-12, 2019
Don't Count on Poisson!
While popular, the Poisson distribution is not always an appropriate choice to model count data. Statistical methods have been broadened to model dispersed count data, through the use of the Conway-Maxwell-Poisson distribution.
Computing in R
Researchers can analyze their dispersed count data via various R packages available on the Comprehensive R Archive Network (CRAN).
Proteomic Data Analysis
Statistical analyses help scientists detect statistically significant differential protein expression and modification (e.g. due to disease onset).
Research Interests
Current research centers on statistical methods and computing associated with generalized statistical methods involving count data that contain data dispersion. Previous research considered image analysis techniques (particularly low-level analyses including preprocessing, normalization, feature detection, and alignment), and reliability theory.
Kimberly F. Sellers306 St. Mary's Hall37th and O Streets, NW; Washington, DC 20057Phone: 202-687-8829Fax: 202-687-6067kfs7@georgetown.edu