Sign test of independence between two random vectors

By Sara Taskinen, Annaliisa Kankainen, Hannu Oja. 2003

52 citations recorded by the source corpus.

Subfields: Geometry and Topology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7aa32048d4f56e29b3082c8bdcdb63f7219922ce

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Geometry and Topology

1. Fang Han
2. Han Liu
3. Bodhisattva Sen
4. Nabarun Deb
5. Ronald H. Randles
6. Hannu Oja
7. Sara Taskinen

In Statistics and Probability

1. Fang Han
2. Nabarun Deb
3. Bodhisattva Sen
4. Han Liu
5. Hannu Oja
6. Sara Taskinen
7. Ronald H. Randles
8. Mathias Drton

Citations in the corpus

• Multivariate Nonparametric Tests of Independence (2005, methodology): “We use similar sequences of alternatives as those used by Gieser and Randles (1997) and Taskinen et al. (2003a).”
• Multivariate Rank-Based Distribution-Free Nonparametric Testing Using Measure Transportation (2019, methodology): “Such coordinate-wise rank-based extensions to Spearman’s rank correlation, Kendall’s τ and the quadrant statistic (mentioned above) for testing independence, when d1 > 1 or d2 > 1, were proposed in Taskinen, Kankainen, and Oja (2003), Taskinen, Oja, and Randles (2005).”
• ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions (2013, methodology): “…efficiency properties of ECA in low dimensions Some related methods using multivariate rank-based statistics are discussed by Tyler (1982), Tyler (1987), Taskinen, Kankainen, and Oja (2003), Oja and Randles (2004), Oja and Paindaveine (2005), Oja et al. (2006), and Sirkiä, Taskinen, and Oja (2007).”