A Kernel Log-Rank Test of Independence for Right-Censored Data

DOI10.1080/01621459.2021.1961784arXiv1912.03784OpenAlexW3184057842MaRDI QIDQ6165281

Tamara Fernández, Unnamed Author, Arthur Gretton, Dino Sejdinovic

Publication date: 4 July 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.03784

zbMATH Keywords

Hilbert spacereproducing kernellog-rank testright-censoringindependence testing

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

A nonparametric test for comparing survival functions based on restricted distance correlation

Cites Work

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• Nonparametric survival analysis with time-dependent covariate effects: A penalized partial likelihood approach
• Nonparametric estimation of partial transition probabilities in multiple decrement models
• Random quadratic forms and the bootstrap for \(U\)-statistics
• Large-scale kernel methods for independence testing
• An omnibus test for independence of a survival time from a covariate
• Adaptive test of independence based on HSIC measures
• Max-type rank tests, \(U\)-tests, and adaptive tests for the two-sample location problem -- an asymptotic power study
• Non‐parametric Tests for Censored Data
• A class of rank test procedures for censored survival data
• Approximation Theorems of Mathematical Statistics
• IX. On the problem of the most efficient tests of statistical hypotheses
• A reproducing kernel Hilbert space log‐rank test for the two‐sample problem
• Universality, Characteristic Kernels and RKHS Embedding of Measures

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