A new maximum mean discrepancy based two-sample test for equal distributions in separable metric spaces
DOI10.1007/S11222-024-10483-9zbMATH Open1545.62164MaRDI QIDQ6606979
Jin-Ting Zhang, Zhi Peng Ong, Bu Zhou
Publication date: 17 September 2024
Published in: Statistics and Computing (Search for Journal in Brave)
high-dimensional datareproducing kernel Hilbert spacetwo-sample testfunctional data\(\chi^2\)-approximationcharacteristic reproducing kernel
Computational methods for problems pertaining to statistics (62-08) Asymptotic distribution theory in statistics (62E20) Functional data analysis (62R10) Hypothesis testing in multivariate analysis (62H15)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Two-sample test statistics for measuring discrepancies between two multivariate probability density functions using kernel-based density estimates
- Applied functional data analysis. Methods and case studies
- A note on the unbiased estimator of \(\mathbf{\Sigma}^2\)
- Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data
- Two-sample test for equal distributions in separate metric space: New maximum mean discrepancy based approaches
- A distribution-free two-sample run test applicable to high-dimensional data
- Approximation Theorems of Mathematical Statistics
- A Hilbert Space Embedding for Distributions
- Asymptotic normality of interpoint distances for high-dimensional data with applications to the two-sample problem
- A Simple Two-Sample Test in High Dimensions Based on L2-Norm
- Universality, Characteristic Kernels and RKHS Embedding of Measures
- Approximate and Asymptotic Distributions of Chi-Squared–Type Mixtures With Applications
- Testing equality of several distributions in separable metric spaces: a maximum mean discrepancy based approach
- A two-sample distribution-free test for functional data with application to a diffusion tensor imaging study of multiple sclerosis
This page was built for publication: A new maximum mean discrepancy based two-sample test for equal distributions in separable metric spaces
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6606979)
