Hilbert space embeddings of independence tests of several variables

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1. Verfasser: Guella, Jean Carlo
Format: Preprint
Veröffentlicht: 2024
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author Guella, Jean Carlo
author_facet Guella, Jean Carlo
contents In this paper, we present the general theory of embedding independence tests on Hilbert spaces that generalizes the concepts of distance covariance, distance multivariance and HSIC. This is done by defining new types of kernel on an $n$ Cartesian product called positive definite independent of order $k$. An emphasis is given on the continuous case in order to obtain a version of the Kernel Mean Embedding for this new classes of kernels. We also provide $2$ explicit methods to construct examples for this new type of kernel on a general space by using Bernstein functions of several variables and completely monotone functions of higher order.
format Preprint
id arxiv_https___arxiv_org_abs_2411_08653
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hilbert space embeddings of independence tests of several variables
Guella, Jean Carlo
Functional Analysis
Probability
30L05, 43A35, 44A10, 46H20
In this paper, we present the general theory of embedding independence tests on Hilbert spaces that generalizes the concepts of distance covariance, distance multivariance and HSIC. This is done by defining new types of kernel on an $n$ Cartesian product called positive definite independent of order $k$. An emphasis is given on the continuous case in order to obtain a version of the Kernel Mean Embedding for this new classes of kernels. We also provide $2$ explicit methods to construct examples for this new type of kernel on a general space by using Bernstein functions of several variables and completely monotone functions of higher order.
title Hilbert space embeddings of independence tests of several variables
topic Functional Analysis
Probability
30L05, 43A35, 44A10, 46H20
url https://arxiv.org/abs/2411.08653