BIOSTATISTICS--MODELING AND INFERENCE

我们提出的研究都与极端相关 计算机密集统计在癌症研究中的应用 医学问题和生理学。 Olshen提出用树形结构的方法来研究问题， 样本再利用技术。特别是，他建议学习和 一种产生无偏估计的技术的实现 在分类树的终端节点内，并研究 样品再利用方法的分层和重新设计。 关于树结构方法的渐近结果的研究 它结合了拆分规则和费率的适应性 文中还讨论了算法的收敛问题。 弗雷德金和赖斯建议发展方法论 恢复有噪声的单通道膜片钳数据。各种各样的 在这方面出现了问题：通过以下方式正确处理过滤 反卷积，基于数据的平滑参数估计， 算法和计算机代码的扩展以处理多个 电导水平通道，以及处理的特殊方法 一闪一闪。我们会特别注意发展 高效的计算机代码。 艾布拉姆森建议进一步研究使用递归技术 在条件分析模型中，有大量的 符合以下条件的影响数量(例如，基线测量) 不是主要感兴趣的和少量的固定效果 是。他建议为将军开发精致的软件 分发。

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.