FADPclust: Functional Data Clustering Using Adaptive Density Peak Detection

An implementation of a clustering algorithm for functional data based on adaptive density peak detection technique, in which the density is estimated by functional k-nearest neighbor density estimation based on a proposed semi-metric between functions. The proposed functional data clustering algorithm is computationally fast since it does not need iterative process. (Alex Rodriguez and Alessandro Laio (2014) <doi:10.1126/science.1242072>; Xiao-Feng Wang and Yifan Xu (2016) <doi:10.1177/0962280215609948>).

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Package details

AuthorRui Ren <xmurr@stu.xmu.edu.cn>
MaintainerRui Ren <xmurr@stu.xmu.edu.cn>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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FADPclust documentation built on Oct. 8, 2021, 9:08 a.m.