Kernel Tests for One, Two, and K-Sample Goodness-of-Fit: State of the Art and Implementation Considerations-Reference-Cited by-同舟云学术

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Kernel Tests for One, Two, and K-Sample Goodness-of-Fit: State of the Art and Implementation Considerations

Published:2020 Issue: Volume: Page:309-337
ISSN:2524-7735
Container-title:Statistical Modeling in Biomedical Research
language:
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Author:

Chen Yang,Markatou Marianthi

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-33416-1_14

Reference53 articles.

1. Anderson, N. H., Hall, P., & Titterington, D. M. (1994). Two-sample test statistics for measuring discrepancies between two multivariate probability density functions using kernel-based density estimates. Journal of Multivariate Analysis, 50(1), 41–54.

2. Aslan, B., & Zech, G. (2005). Statistical energy as a tool for binning-free, multivariate goodness-of-fit tests, two-sample comparison and unfolding. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 537(3), 626–636.

3. Barakat, A. S., Quade, D., & Salama, I. A. (1996). Multivariate homogeneity testing using an extended concept of nearest neighbors. Biometrical Journal, 38(5), 605–612.

4. Baringhaus, L., & Franz, C. (2004). On a new multivariate two-sample test. Journal of Multivariate Analysis, 88(1), 190–206.

5. Bickel, P. J. (1969). A distribution free version of the smirnov two sample test in the p-variate case. The Annals of Mathematical Statistics, 40(1), 1–23.

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