评论基于形状的功能数据分析

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY
Test Pub Date : 2023-12-13 DOI:10.1007/s11749-023-00907-5
Ian L. Dryden
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引用次数: 0

摘要

讨论的重点是用户在执行基于形状的功能数据分析时所做的不同选择。首先,有一个额外的翘曲处罚的选择,可以包括在程序中。面向对象的数据分析方法可用于选择这种翘曲惩罚,并给出了泥炭地监测中的一个示例。此外,还可以选择分析是在商流形中还是在环境空间中。任何一种策略都有优点和缺点,但在许多例子中,由于拉普拉斯近似,结果是相似的。最后的评论指出,作者提供了许多令人信服的方法和许多有用的见解。很明显,平方根速度函数(SRVF)和传输SRVF方法将在未来解决更多的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comments on: Shape-based functional data analysis

The discussion focuses on the different choices that are made by the user in carrying out shape-based functional data analysis. First, there is the choice of an additional warping penalty that can be included in the procedure. An object-oriented data analysis approach can be useful for selecting such a warping penalty, and an example from monitoring peatland is given. Also, there is a choice to be made about whether the analysis is in a quotient manifold or an ambient space. There are advantages and disadvantages to either strategy, but in many examples, the results are similar due to a Laplace approximation. The final comment states that the authors provide plenty of convincing approaches with many useful insights. It is clear that the square root velocity function (SRVF) and transported SRVF methods will give solutions to many more problems in the future.

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来源期刊
Test
Test 数学-统计学与概率论
CiteScore
2.20
自引率
7.70%
发文量
41
审稿时长
>12 weeks
期刊介绍: TEST is an international journal of Statistics and Probability, sponsored by the Spanish Society of Statistics and Operations Research. English is the official language of the journal. The emphasis of TEST is placed on papers containing original theoretical contributions of direct or potential value in applications. In this respect, the methodological contents are considered to be crucial for the papers published in TEST, but the practical implications of the methodological aspects are also relevant. Original sound manuscripts on either well-established or emerging areas in the scope of the journal are welcome. One volume is published annually in four issues. In addition to the regular contributions, each issue of TEST contains an invited paper from a world-wide recognized outstanding statistician on an up-to-date challenging topic, including discussions.
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