Mathematical Sciences: Innovative Statistical Methods for Biological Life Spans and Oldest-Old Mortality

本文采用基于平滑的非参数风险函数估计方法研究高龄老人的死亡率 生命表技术二维光顺方法 为词汇图表将开发允许预测人口队列的生存，采用内核和本地 加权最小二乘平滑器。 男女比较， 死亡率水平的变化将被调查， 变点技术样本的随机过程模型 将介绍寿命表和相关推论。 计划分析各种生物学和人口统计学 数据集，特别是一个巨大的集合， 关于地中海果蝇生存的数据。 在这个跨学科的项目中，新开发的非参数 统计技术将被应用于处理一个复杂的， 关于长寿的生物学和人口学问题， 人口中最老部分的死亡率。这些 问题集中在死亡率是否在下降 最古老的部分或总是随着年龄的增长，如何性别差异 影响死亡率的变化，以及在多大程度上可以预测未来 死亡率和预期寿命。这些问题之所以重要，是因为它们可能对社会规划产生影响， 未来以及衰老生物学。攻击这些 这些问题需要发展新的统计方法和创新地应用现有的统计方法 来分析当前的生物实验和人口统计数据

We investigate mortality of the oldest-old by means of nonparametric hazard function estimation based on smoothing techniques for lifetables. Two- dimensional smoothing methods for Lexis diagrams will be developed allowing to predict the survival of demographic cohorts, employing kernel and locally weighted least squares smoothers. Male-female comparisons and changes in the level of mortality will be investigated with change-point techniques. Stochastic process models for samples of lifetables and associated inference will be introduced. It is planned to analyze various biological and demographic data sets with these methods, in particular a huge set of data on the survival of medflies. In this interdisciplinary project, newly developed nonparametric statistical techniques will be applied to approach a complex of biological and demographic qu estions about longevity and mortality of the oldest segment of the population. These questions focus on whether mortality is decreasing for the oldest segment or is invariably increasing with age, how sex differences affect changes in mortality, and to what degree one can predict future mortality and life expectation from current trends. The importance of these problems derives from their potential impact on social planning for the future as well as on the biology of aging. Attacking these problems requires the development of new statistical methods and the innovative application of existing statistical methods to analyze current biological experiments and demographic data