The research we propose is all connected with extremely computer intensive statistics applied to cancer research, other medical problems and physiology. Olshen proposes studying problems in tree-structured methods and sample reuse techniques. In particular, he proposes study and implementation of a technique for producing unbiased estimates within the terminal nodes of a classification tree, and study of stratification and redesign of sample reuse methods. Investigations of asymptotic results on tree-structured methods that incorporate adaptiveness of splitting rules and rates of convergence for the algorithms are also proposed. Fredkin and Rice propose development of methodology for restoration of noisy single channel patch clamp data. A variety of issues arise in this regard: proper handling of filtering via deconvolution, data-based smoothing parameter estimates, extension of algorithms and computer code to handle multi conductance level channels, and special methods for dealing with flickering. Special attention will be given to the development of efficient computer code. Abramson proposes further study of a recursive technique for use in conditional analysis of models in which there are a large number of effects (for example, baseline measurements) that are not of primary interest and a small number of fixed effects that are. He proposes development of polished software for general distribution.
