Katherine Bennett Ensor

Associate Professor of Statistics

Time Series, Spatial Processes, Simulation-Based Estimation

B.S.E. (1981) Arkansas State University

M.S. (1982) Arkansas State University

Ph. D. (1986) Texas A&M University


Professor Ensor has a variety of interests in the field of statistics. Much of her theoretical research originates from interdisciplinary problems such as tissue discrimination in magnetic resonance imaging (MRI). Since models for MRI are highly nonlinear, many statistical issues arise regarding estimation of their parameters. Professor Ensor has developed a model selection method that accurately identifies the complexity that the MRI data can support. She is now incorporating use of this method in techniques for tissue discrimination.

In the field of environmental statistics, Professor Ensor is currently working with colleagues at Rice on various problems in groundwater contamination. She is also working with a consortium of Texas statisticians from Rice, other academic institutions, and the Texas Natural Resource Conservation Commission to investigate the growing problem of air quality in the state and specifically within the Houston area. Goals of this multifaceted work are to develop methods for categorical time series, to develop estimation methods incorporating both time and space that allow for missing observations, to develop a model for predicting high ambient ozone levels, and to develop multidimensional graphical methods for displaying the large amount of information.

Professor Ensor has developed computer intensive estimation procedures for complicated stochastic processes. This work enables scientists in other fields to utilize structural stochastic models that often are discarded because of their statistical complexity, not because of model inaccuracies. Ongoing work in this area focuses on obtaining the optimal estimator through simulation-based estimation. The goal is to develop software that will find the best estimates for any stochastic model.


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