Tests of mutual independence among several random vectors using univariate and multivariate ranks of nearest neighbours
From MaRDI portal
Publication:5065310
DOI10.1080/00949655.2021.1876060OpenAlexW3128511548MaRDI QIDQ5065310
Kunal Das, Angshuman Roy, Soham Sarkar, Anil Kumar Ghosh
Publication date: 18 March 2022
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2021.1876060
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Measuring and testing dependence by correlation of distances
- Generalizing Distance Covariance to Measure and Test Multivariate Mutual Dependence
- On some exact distribution-free tests of independence between two random vectors of arbitrary dimensions
- A class of multivariate distribution-free tests of independence based on graphs
- A multivariate version of Hoeffding's phi-square
- Graph-theoretic measures of multivariate association and prediction
- Sign test of independence between two random vectors.
- Multivariate nonparametric test of independence
- Nonparametric tests of independence between random vectors
- Multivariate versions of Blomqvist's beta and Spearman's footrule
- A multivariate empirical characteristic function test of independence with normal marginals
- A sharper Bonferroni procedure for multiple tests of significance
- A Nonparametric Test of Independence Between Two Vectors
- Kernel-Based Tests for Joint Independence
- Distance Metrics for Measuring Joint Dependence with Application to Causal Inference
- A consistent multivariate test of association based on ranks of distances
- Multivariate Nonparametric Tests of Independence
This page was built for publication: Tests of mutual independence among several random vectors using univariate and multivariate ranks of nearest neighbours
