Bayesian model selection with fractional Brownian motion
(2018) In Journal of Statistical Mechanics: Theory and Experiment- Abstract
- We implement Bayesian model selection and parameter estimation for the case of fractional Brownian motion with measurement noise and a constant drift. The approach is tested on artificial trajectories and shown to make estimates that match well with the underlying true parameters, while for model selection the approach has a preference for simple models when the trajectories are finite. The approach is applied to observed trajectories of vesicles diffusing in Chinese hamster ovary cells. Here it is supplemented with a goodness-of-fit test, which is able to reveal statistical discrepancies between the observed trajectories and model predictions.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/71bda097-c9ff-44b0-a7e5-70ccf4957c58
- author
- Krog, Jens LU ; Jacobsen, Lars H ; Lund, Frederik W ; Wüstner, Daniel and Lomholt, Michael A.
- publishing date
- 2018-09-18
- type
- Contribution to journal
- publication status
- published
- in
- Journal of Statistical Mechanics: Theory and Experiment
- publisher
- IOP Publishing
- external identifiers
-
- scopus:85054704941
- ISSN
- 1742-5468
- DOI
- 10.1088/1742-5468/aadb0e
- language
- English
- LU publication?
- no
- id
- 71bda097-c9ff-44b0-a7e5-70ccf4957c58
- date added to LUP
- 2019-05-28 10:36:00
- date last changed
- 2022-04-26 00:47:40
@article{71bda097-c9ff-44b0-a7e5-70ccf4957c58, abstract = {{We implement Bayesian model selection and parameter estimation for the case of fractional Brownian motion with measurement noise and a constant drift. The approach is tested on artificial trajectories and shown to make estimates that match well with the underlying true parameters, while for model selection the approach has a preference for simple models when the trajectories are finite. The approach is applied to observed trajectories of vesicles diffusing in Chinese hamster ovary cells. Here it is supplemented with a goodness-of-fit test, which is able to reveal statistical discrepancies between the observed trajectories and model predictions.}}, author = {{Krog, Jens and Jacobsen, Lars H and Lund, Frederik W and Wüstner, Daniel and Lomholt, Michael A.}}, issn = {{1742-5468}}, language = {{eng}}, month = {{09}}, publisher = {{IOP Publishing}}, series = {{Journal of Statistical Mechanics: Theory and Experiment}}, title = {{Bayesian model selection with fractional Brownian motion}}, url = {{http://dx.doi.org/10.1088/1742-5468/aadb0e}}, doi = {{10.1088/1742-5468/aadb0e}}, year = {{2018}}, }