Thursday, June 6 at 7:00 p.m.
Office: 325 Machray Hall
My research has primarily been in Bayesian statistics and statistical decision theory. I have been doing research in decision theoretic problems related to the theory and applications of balanced type loss functions as well as estimation in constrained parameter spaces. Recently I have developed an interest in research related to ranked set sampling (RSS) from finite and infinite populations. RSS is typically used when it is very expensive to collect data on the variables of interest (e.g., in fisheries, agriculture, environmental and ecological studies, economy) but a reasonable number of the sampling units can be ordered (partially) with respect to a variable of interest without actual measurement and at little cost. For example, in fisheries studies aging the fish is time consuming and requires substantial scientific process. But a sample of fish could be ranked easily based on their lengths. RSS designs provide a collection of techniques to obtain more representative samples in these situations with the help of the available auxiliary information. My current research in RSS involves drawing design-based and model-based inference including parametric and nonparametric studies based on RSS and some its modifications which I developed with my collaborators (e.g., randomized nomination sampling; RSS with antithetic variables).