專題演講 主講人：張馨文博士 (中央研究院統計所)
題 目：A non-smoothing framework for inference on functional means
主講人：張馨文博士 (中央研究院統計所)
時 間：112年5月12日(星期五)上午10:40-11:30
(上午10:20-10:40茶會於綜合一館428室舉行)
地 點：綜合一館427室
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摘要
This talk introduces a nonparametric inference framework that is applicable to occupation time curves derived from wearable device data. Motivated by the right-continuity of these curves, we develop a non-smoothing approach that involves weaker conditions than existing conditions imposed when using smoothing to estimate functional means under a fixed dense design. Notably, our procedure allows discontinuities in the functional covariances while accommodating discretization of the observed trajectories. Under this non-smoothing framework, we devise an empirical likelihood method to construct confidence bands for the functional means. Our method utilizes the known optimality of empirical likelihood. It also respects range and monotonicity constraints on occupation time curves. A simulation study shows that the proposed procedures outperform competing functional data procedures. We illustrate the proposed methods using wearable device data from an NHANES study.
