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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 tuned...
Consider an autoregressive model with measurement error: we observe
=
+
, where the unobserved
is a stationary solution of the autoregressive equation
=
(
) +
. The regression function
is known up to a finite dimensional parameter
to be estimated. The distributions of
and
are unknown and
...
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