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KmL:用于聚类纵向数据的软件包。

KmL: a package to cluster longitudinal data.

机构信息

Inserm, U669, Paris, France.

出版信息

Comput Methods Programs Biomed. 2011 Dec;104(3):e112-21. doi: 10.1016/j.cmpb.2011.05.008. Epub 2011 Jun 25.

Abstract

Cohort studies are becoming essential tools in epidemiological research. In these studies, measurements are not restricted to single variables but can be seen as trajectories. Thus, an important question concerns the existence of homogeneous patient trajectories. KmL is an R package providing an implementation of k-means designed to work specifically on longitudinal data. It provides several different techniques for dealing with missing values in trajectories (classical ones like linear interpolation or LOCF but also new ones like copyMean). It can run k-means with distances specifically designed for longitudinal data (like Frechet distance or any user-defined distance). Its graphical interface helps the user to choose the appropriate number of clusters when classic criteria are not efficient. It also provides an easy way to export graphical representations of the mean trajectories resulting from the clustering. Finally, it runs the algorithm several times, using various kinds of starting conditions and/or numbers of clusters to be sought, thus sparing the user a lot of manual re-sampling.

摘要

队列研究正在成为流行病学研究中不可或缺的工具。在这些研究中,测量不仅限于单一变量,而可以被视为轨迹。因此,一个重要的问题是存在同质的患者轨迹。KmL 是一个 R 包,提供了 k-均值的实现,专门用于处理纵向数据。它提供了几种不同的技术来处理轨迹中的缺失值(例如线性插值或 LOCF 等经典技术,以及复制均值等新技术)。它可以使用专门为纵向数据设计的距离运行 k-均值(例如 Frechet 距离或任何用户定义的距离)。其图形界面有助于用户在经典标准无效时选择适当的聚类数量。它还提供了一种简单的方法来导出聚类产生的平均轨迹的图形表示。最后,它会多次运行算法,使用各种起始条件和/或要搜索的聚类数量,从而为用户节省了大量的手动重新采样。

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