Parametric inference for mixed models defined by stochastic differential equations

@inproceedings{Donnet2007ParametricIF,
  title={Parametric inference for mixed models defined by stochastic differential equations},
  author={Sophie Donnet and Adeline Samson},
  year={2007}
}
Non-linear mixed models defined by stochastic differential equations (SDEs) are considered: the parameters of the diffusion process are random variables and vary among the individuals. A maximum likelihood estimation method based on the Stochastic Approximation EM algorithm, is proposed. This estimation method uses the Euler-Maruyama approximation of the diffusion, achieved using latent auxiliary data introduced to complete the diffusion process between each pair of measurement instants. A… CONTINUE READING

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