activity
20192021
most citedQuantifying model uncertainty for the observed non-Gaussian data by the Hellinger distance

7 citations · 12 across the 3 of their papers we have counts for

collaborators

5 papers

math.DS2021

A representation formula for the probability density in stochastic dynamical systems with memory

Fang Yang, Xu Sun

Marcus stochastic delay differential equations (SDDEs) are often used to model stochastic dynamical systems with memory in science and engineering. Since no infinitesimal generator…

math.DS20205 cited

On the abrupt change of the maximum likelihood state in a simplified stochastic thermohaline circulation system

Fang Yang, Xu Sun, Jinqiao Duan

The maximum likelihood state for a simplified stochastic thermohaline circulation model is investigated. It is shown that a jump occurs for the maximum likelihood state during tran…

math.DS20207 cited

Quantifying model uncertainty for the observed non-Gaussian data by the Hellinger distance

Yayun Zheng, Fang Yang, Jinqiao Duan +1

Mathematical models for complex systems under random fluctuations often certain uncertain parameters. However, quantifying model uncertainty for a stochastic differential equation…

physics.ao-ph2020

The tipping times in an Arctic sea ice system under influence of extreme events

Fang Yang, Yayun Zheng, Jinqiao Duan +2

In light of the rapid recent retreat of Arctic sea ice, the extreme weather events triggering the variability in Arctic ice cover has drawn increasing attention. A non-Gaussian

cond-mat.stat-mech2019

The maximum likelihood climate change for global warming under the influence of greenhouse effect and Lévy noise

Yayun Zheng, Fang Yang, Jinqiao Duan +3

An abrupt climatic transition could be triggered by a single extreme event, an -stable non-Gaussian Lévy noise is regarded as a type of noise to generate such extreme events. In…