An introduction with medical applications to functional data analysis
An introduction with medical applications to functional data analysis
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DOI：
10.1002/sim.5989
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发表时间：
2013-12-30
影响因子：
2
通讯作者：
Sangalli, Laura M.
中科院分区：
文献类型：
--
作者：
Sorensen, Helle;Goldsmith, Jeff;Sangalli, Laura M.
函数数据是可以由合适的函数表示的数据，例如曲线（可能是多维的）或曲面。本文介绍了一些基本的，但重要的技术，用于分析这样的数据，我们将这些技术应用于两个数据集的生物医学。一个数据集是关于多发性硬化症患者大脑中的白色物质结构;另一个数据集是关于为研究脑动脉瘤而收集的三维血管几何形状。所描述的技术是平滑，对齐，主成分分析和回归。版权所有（c）2013约翰威利父子有限公司
Functional data are data that can be represented by suitable functions, such as curves (potentially multi-dimensional) or surfaces. This paper gives an introduction to some basic but important techniques for the analysis of such data, and we apply the techniques to two datasets from biomedicine. One dataset is about white matter structures in the brain in multiple sclerosis patients; the other dataset is about three-dimensional vascular geometries collected for the study of cerebral aneurysms. The techniques described are smoothing, alignment, principal component analysis, and regression. Copyright (c) 2013 John Wiley & Sons, Ltd.