Parameter estimation of linear stochastic differential equations with sparse observations

HIGHLIGHTS

• who: Yuecai Han and colleagues from the School of Mathematics, Jilin University, Changchun, China have published the research: Parameter Estimation of Linear Stochastic Differential Equations with Sparse Observations, in the Journal: Symmetry 2022, 14, 2500. of /2022/
• what: The authors develop a computationally efficient method to deal with the observations with infrequent and irregularly spaced follow-up times. The authors propose a method that formalizes the forwarding and lagging strategy, with kernel weighting enabling the use of all available forward and lagged observations. In this section, utilizing both forward and backward-lagged observation, the authors . . .
  

   

  

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