个体水平模型的事件发生时间非参数抽样 (NPS) 计算效率方法

medRxiv - Health Policy Pub Date : 2024-04-07 DOI:10.1101/2024.04.05.24305356

David Garibay, Hawre Jalal, Fernando Alarid-Escudero

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引用次数: 0

摘要

目的个体级仿真模型通常需要对事件发生的时间进行采样，但许多过程的有效参数分布往往并不存在。例如，生命表中的死亡时间无法从现有的参数分布中准确采样。我们提出了一种高效的非参数方法来对事件发生时间进行采样，这种方法不需要对危害进行任何参数假设。

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A computationally efficient nonparametric sampling (NPS) method of time to event for individual-level models

Purpose Individual-level simulation models often require sampling times to events, however efficient parametric distributions for many processes may often not exist. For example, time to death from life tables cannot be accurately sampled from existing parametric distributions. We propose an efficient nonparametric method to sample times to events that does not require any parametric assumption on the hazards.

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medRxiv - Health Policy

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