Adaptive Exponential Power Depth with Application to Classification
Adaptive Exponential Power Depth with Application to Classification
复制标题
自适应指数幂深度及其在分类中的应用
DOI：
10.1007/s00357-018-9264-z
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发表时间：
2018-10
影响因子：
2
通讯作者：
Wang Xueqin
中科院分区：
文献类型：
--
作者：
Jiang Yunlu;Wen Canhong;Wang Xueqin
Depth functions have many applications in multivariate data analysis, including discriminant analysis and classification. In this paper, we introduce a novel class of data depth: exponential power depth (EPD) functions. Under some conditions, we show that the EPD functions are a statistical depth function, and the sample EPD functions are consistent and asymptotically normal. Based on the proposed EPD functions, we construct a DD-plot (depth-versus-depth plot), which can be applied to the classification problem. Since the EPD functions contain the two tuning parameters, we provide a data-driven approach to select these tuning parameters. The simulation studies and two real data analysis are conducted to assess the finite sample performance of the proposed method.
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DOI：
--
发表时间：
1936
期刊：
--
影响因子：
--
作者：
P. Mahalanobis
通讯作者：
P. Mahalanobis
影响因子：
2
作者：
C. Small
通讯作者：
C. Small
影响因子：
1.5
作者：
A. Ghosh;P. Chaudhuri
通讯作者：
A. Ghosh;P. Chaudhuri
DOI：
10.1002/9780470316481
发表时间：
1980
期刊：
--
影响因子：
--
作者：
Ing Rj Ser
通讯作者：
Ing Rj Ser
影响因子：
1.3
作者：
R. Fraiman;J. Meloche;L. García-Escudero;A. Gordaliza;Xuming He;R. Maronna;V. Yohai;S. Sheather;J. McKean;C. Small;A. Wood;R. Fraiman
通讯作者：
R. Fraiman;J. Meloche;L. García-Escudero;A. Gordaliza;Xuming He;R. Maronna;V. Yohai;S. Sheather;J. McKean;C. Small;A. Wood;R. Fraiman