Analysis of distance matrices
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DOI: 10.1016/j.spl.2022.109720
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References listed on IDEAS
- Peter Hall & J. S. Marron & Amnon Neeman, 2005. "Geometric representation of high dimension, low sample size data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(3), pages 427-444, June.
- Jun Li, 2018. "Asymptotic normality of interpoint distances for high-dimensional data with applications to the two-sample problem," Biometrika, Biometrika Trust, vol. 105(3), pages 529-546.
- Lingzhe Guo & Reza Modarres, 2019. "Interpoint Distance Classification of High Dimensional Discrete Observations," International Statistical Review, International Statistical Institute, vol. 87(2), pages 191-206, August.
- Reza Modarres, 2020. "Graphical Comparison of High‐Dimensional Distributions," International Statistical Review, International Statistical Institute, vol. 88(3), pages 698-714, December.
- Reza Modarres, 2022. "Nonparametric tests for detection of high dimensional outliers," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 34(1), pages 206-227, January.
- Marco Marozzi & Amitava Mukherjee & Jan Kalina, 2020. "Interpoint distance tests for high-dimensional comparison studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(4), pages 653-665, March.
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Keywords
Interpoint distance; Dissimilarity; HDLSS; Outlier; Change point;All these keywords.
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