Research Interests

Small Area Estimation:

Small area estimation seeks to provide reliable and accurate estimates when sample sizes are small.  Linear models can be used to develop such estimates.  My current research studies the performance of several methods of constructing confidence intervals for the means of a linear model through simulation.

Kernel Density Estimation:

I am interested in developing a bivariate extension to a univariate kernel density estimator when the bounds of the data are known.  An example of this type of data comes from the bivariate exponential distribution. 

Minimum Hellinger Distance:

A minimum Hellinger distance estimate (MHDE) is the value that minimizes the distance between a kernel density estimator and a model density.  Such an estimator has very nice properties in terms of efficiency and robustness.  I am interested in studying MHDE’s in a multivariate context.  One such application is for the bivariate exponential distribution previously mentioned.  I am also interested in developing a robust approach to the One-way ANOVA using minimum Hellinger distance.