Bias of particle approximations to optimal filter derivative
In many applications, a state-space model depends on a parameter which needs to be inferred from data in an online manner. In the maximum likelihood approach, this can be achieved using stochastic gradient search, where the underlying gradient estimation is based on the optimal filter and the optima...
Main Authors: | Tadic, VZB, Doucet, A |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Society for Industrial and Applied Mathematics
2021
|
Similar Items
-
Stability of optimal filter higher-order derivatives
by: Tadić, VZB, et al.
Published: (2020) -
Stability of optimal filter higher-order derivatives
by: Tadic, VZB, et al.
Published: (2020) -
Asymptotic properties of recursive particle maximum likelihood estimation
by: Tadic, VZB, et al.
Published: (2019) -
Asymptotic properties of recursive particle maximum likelihood estimation
by: Tadic, VZB, et al.
Published: (2020) -
Optimisation of particle filters using simultaneous perturbation stochastic approximation
by: Chan, T, et al.
Published: (2003)