Smoothed Weighted Quantile Regression for Censored Data in Survival Analysis

Smoothed Weighted Quantile Regression for Censored Data in Survival Analysis

In this study, we propose a smoothed weighted quantile regression (SWQR), which combines convolution smoothing with a weighted framework to address the limitations. By smoothing the non-differentiable quantile regression loss function, SWQR can improve computational efficiency and allow for more sta...

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Bibliographic Details
Main Authors: Kaida Cai, Hanwen Liu, Wenzhi Fu, Xin Zhao
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Axioms
Subjects:
quantile regression
convolution smoothing
survival analysis
right censoring
gradient-based optimization
Online Access:https://www.mdpi.com/2075-1680/13/12/831

Internet

https://www.mdpi.com/2075-1680/13/12/831

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