abc-sde: A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models
(2013)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4216223
- author
- Picchini, Umberto LU
- organization
- publishing date
- 2013
- type
- Other contribution
- publication status
- published
- subject
- language
- English
- LU publication?
- yes
- additional info
- Funded by the Faculty of Science at Lund University under the grant "Money Tools" (verktygspengar). A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459
- id
- 2fa1f35f-cdf0-4d5b-9042-7917c965ff30 (old id 4216223)
- alternative location
- http://sourceforge.net/projects/abc-sde/
- date added to LUP
- 2016-04-04 13:43:28
- date last changed
- 2018-11-21 21:15:52
@misc{2fa1f35f-cdf0-4d5b-9042-7917c965ff30, author = {{Picchini, Umberto}}, language = {{eng}}, title = {{abc-sde: A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models}}, url = {{http://sourceforge.net/projects/abc-sde/}}, year = {{2013}}, }