Mathematical Sciences: Problems in Mathematical Statistics

将对数据驱动平滑进行研究 参数选择和变异性评估 非参数曲线估计 将制定方法 对于序列分析中的自由边界问题， 特别是对于一般的优先权。 将试图 为“轰炸机问题”建立一个猜想（关于 国防拨款率）。对一般问题的初步研究 估计失真的方法将应用于加密。 在 数据网格被未知的自然属性划分的情况 将数据分为两个同类组的边界， 非参数方法估计的边界将进行研究。 处理相关观测和重尾 观察，研究将进行修改， bootstrap是一种非参数技术， 统计量的抽样分布。

Research will be conducted on data-driven smoothing parameter selection and assessment of the variability of nonparametric curve estimators. Methodology will be developed for the free boundary problem in sequential analysis, particularily for general priors. Attempts will be made to establish a conjecture for the "bomber problem" (concerning defense allocation rates). A pilot study for the general problem of estimating distortion will be applied to encryption. In the case that a grid of data is partitioned by an unknown natural boundary that separates data into two homogeneous groups, a nonparametric method for estimating the boundary will be studied. To deal with dependent observations and heavy-tailed observations, research will be carried out on modifications of the bootstrap, a nonparametric technique for modelling the sampling distribution of a statistic.