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实体 Continuous-time stochastic processes for the spread of COVID-19 disease simulated via a Monte Carlo approach and comparison with deterministic models

Continuous-time stochastic processes for the spread of COVID-19 disease simulated via a Monte Carlo approach and comparison with deterministic models

PulseAugur coverage of Continuous-time stochastic processes for the spread of COVID-19 disease simulated via a Monte Carlo approach and comparison with deterministic models — every cluster mentioning Continuous-time stochastic processes for the spread of COVID-19 disease simulated via a Monte Carlo approach and comparison with deterministic models across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_344349 ·

    新框架将工具变量扩展到连续时间因果推断

    研究人员开发了一种新的工具变量（IV）方法框架，可应用于连续时间随机过程。该框架解决了在存在未观测混淆因素的情况下，识别随时间演变系统中的因果效应的挑战。该方法在随机微分方程的漂移的无穷小层面编码因果效应，并提供了一个识别条件和估计方法，在实证测试中已被证明优于传统的最大似然法和离散时间IV方法。