Ctrl K

Partile filter code with an example of weight collapse in importance sampling methods

Partile filter code with an example of weight collapse in importance sampling methods

1
contributor

Description

We propose an implementation of the particle filter in a quasi-static case in the example of Gaussian prior with independent and identically distributed prior states and observation errors. Weight collapse occurs in the particle filter when the number of model states and observations increases for a given ensemble size. In this example, we use a synthetic experiment to illustrate how weight collapse varies in the posterior distribution.

This code provides a basis for the implementation of importance sampling methods and can be easily adapted to other problems.

Logo of Partile filter code  with an example of weight collapse in importance sampling methods
Keywords
Data assimilation
Importance sampling
Particle method
Subsidence
Weight collapse
Programming languages
License
  • MIT
</>Source code
Packages

Contributors

SK
Samantha Kim

Member of community

4TU