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Updated: Aug 9, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Generalized Survival Probability.

David A Zarate-Herrada¹, Lea F Santos², E Jonathan Torres-Herrera¹

¹Instituto de Física, Benemérita Universidad Autónoma de Puebla, Apartado Postal J-48, Puebla 72570, Mexico.

Entropy (Basel, Switzerland)

|February 25, 2023

Summary

This study introduces a generalized survival probability, inspired by generalized entropies, to analyze nonergodic systems. This new measure aids in understanding eigenstate structures and system ergodicity.

Keywords:

disordered spin model many-body quantum chaos quench dynamics spectral form factor survival probability

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Area of Science:

Statistical Mechanics
Quantum Physics
Complex Systems

Background:

Survival probability quantifies the likelihood of a system remaining in its initial state after being perturbed.
Nonergodic states present challenges in traditional statistical analysis due to their complex dynamics.

Purpose of the Study:

Introduce a generalized survival probability (GSP) to enhance the analysis of nonergodic systems.
Explore the utility of GSP in characterizing eigenstate structures and ergodicity.

Main Methods:

Leveraging concepts from generalized entropies.
Developing a theoretical framework for the generalized survival probability.

Main Results:

The proposed generalized survival probability offers a novel approach to studying complex system dynamics.
Demonstrated potential of GSP in distinguishing between different types of nonergodic behavior.

Conclusions:

Generalized survival probability provides a powerful tool for investigating the structure of eigenstates.
This generalization advances the understanding of ergodicity in complex systems.