ResearchTrend.AI
A test for Gaussianity in Hilbert spaces via the empirical characteristic functional

A test for Gaussianity in Hilbert spaces via the empirical characteristic functional

N. Henze
M. D. Jiménez-Gamero
ArXiv (abs)PDFHTML

Papers citing "A test for Gaussianity in Hilbert spaces via the empirical characteristic functional"

5 / 5 papers shown
Title
Eigenvalues approximation of integral covariance operators with applications to weighted $L^2$ statistics
Eigenvalues approximation of integral covariance operators with applications to weighted L2L^2 statistics
Bruno Ebner
M. D. Jiménez-Gamero
Bojana Milošević
48
0
0
15 Aug 2024
Specification procedures for multivariate stable-Paretian laws for independent and for conditionally heteroskedastic data
Specification procedures for multivariate stable-Paretian laws for independent and for conditionally heteroskedastic data
S. Meintanis
John P. Nolan
C. Pretorius
124
3
0
20 Oct 2023
A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces
A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces
George Wynne
Mikolaj Kasprzak
Andrew B. Duncan
110
4
0
09 Jun 2022
Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and Depth in Functional Data Analysis
Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and Depth in Functional Data Analysis
George Wynne
Stanislav Nagy
96
6
0
26 May 2021
On combining the zero bias transform and the empirical characteristic function to test normality
On combining the zero bias transform and the empirical characteristic function to test normality
B. Ebner
55
8
0
27 Feb 2020

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.