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doi: 10.4121/e25786c9-2bad-4408-a5af-41c8218a5fe5

Kim, Samantha (2024): Partile filter code with an example of weight collapse in importance sampling methods. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/e25786c9-2bad-4408-a5af-41c8218a5fe5.v1

Software

• Numerical and Computational Mathematics
• Other Earth Sciences
• Earth Sciences
• Mathematical Sciences

Data assimilation, Importance sampling, Particle method, Subsidence, Weight collapse

MIT

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by Samantha Kim

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.

• 2024-02-20 first online, published, posted

4TU.ResearchData

https://github.com/samanthasrkim/particle_filter_standard

• Monitoring and Modeling the Groningen Subsurface based on integrated Geodesy and Geophysics: improving the space-time dimension (grant code DEEP.NL.2018.052) [more info...] Dutch Research Council

TU Delft, Faculty of Civil Engineering & Geosciences, Department of Geoscience & Engineering