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Local functional data model for characterizing shape variation of similar curves

机译:表征相似曲线形状变化的局部功能数据模型

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摘要

Similar curves in the present article refers to a family of curves whose major shape are similar, but who have variation coming from curve-specific sources. The goal here is to develop a general methodology to describe small changes among similar curves. Previous methods mainly focus on dimension reduction through FPCA, which are not appropriate for quantifying local variation. Here, we consider a local functional data model which divides data into segments adaptively and models each segment with a shape invariant model. Such model has great flexibility in characterizing local variation of curves, as illustrated by simulation and real data examples.
机译:本文中的相似曲线指的是主要形状相似,但其变化来自特定曲线源的一系列曲线。这里的目标是开发一种通用的方法来描述相似曲线之间的细微变化。先前的方法主要集中在通过FPCA进行降维,这不适用于量化局部变化。在这里,我们考虑一个局部功能数据模型,该模型将数据自适应地划分为多个段,并使用形状不变模型对每个段进行建模。如仿真和实际数据示例所示,这种模型在表征曲线的局部变化方面具有很大的灵活性。

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