This paper introduces the sparse functional boxplot and the intensity sparse functional boxplot as practical exploratory tools. Besides being available for complete functional data, they can be used in sparse univariate and multivariate functional data. The sparse functional boxplot, based on the functional boxplot, displays sparseness proportions within the 50\% central region. The intensity sparse functional boxplot indicates the relative intensity of fitted sparse point patterns in the central region. The two-stage functional boxplot, which derives from the functional boxplot to detect outliers, is furthermore extended to its sparse form. We also contribute to sparse data fitting improvement and sparse multivariate functional data depth. In a simulation study, we evaluate the goodness of data fitting, several depth proposals for sparse multivariate functional data, and compare the results of outlier detection between the sparse functional boxplot and its two-stage version. The practical applications of the sparse functional boxplot and intensity sparse functional boxplot are illustrated with two public health datasets. Supplementary materials and codes are available for readers to apply our visualization tools and replicate the analysis.
翻译:本文作为实用的探索工具,介绍稀有的功能框点和密度稀薄的功能框点,作为实用的探索工具。它们除了用于完整的功能数据外,还可以用于稀有的单词框和多变量功能数据。根据功能框点的稀疏功能框点,显示在50 ⁇ 中央区域中的稀疏比例。密度稀疏功能框点显示了中部区域适合的稀疏点模式的相对强度。由功能盒点产生的两阶段功能盒点点进一步扩展至其稀薄的形式。我们还有助于稀少的数据适合改进和稀有的多变量功能数据深度。在模拟研究中,我们评估数据匹配的优劣性、稀疏多变量功能数据的一些深度建议,并比较稀疏功能框点及其两阶段版本之间的异检测结果。稀疏功能盒点和强度稀散功能盒点的实际应用用有两个公共卫生数据集加以说明。为读者提供了补充材料和代码,以应用可视化的工具并复制分析。