# Energy distance and kernel mean embedding for two sample survival test

## TL;DR

This paper introduces new statistical tests for comparing two survival distributions under right censoring, utilizing energy distance and kernel mean embedding, with permutation calibration and proven consistency.

## Contribution

It proposes a novel family of two-sample tests specifically designed for censored survival data, combining energy distance and kernel methods with permutation calibration.

## Key findings

- Tests perform well in finite sample simulations
- They are consistent against all alternatives
- Effective in real survival analysis scenarios

## Abstract

In this article a new family of tests is proposed for the comparison problem of the equality of distribution of two-sample under right censoring scheme. The tests are based on energy distance and kernels mean embedding, are calibrated by permutations and are consistent against all alternatives. The good performance of the new tests in real situations with finite samples is established with a simulation study.