tjhladish/AbcSmc
AbcSmc is a parameter estimation library implemented in C++ that has been developed to enable fitting complex stochastic models to disparate types of empirical data. We use partial least squares to address problems arising from parameters and/or empirical metrics that co-vary or are unidentifiable (parameters) or uninformative (metrics). Because of the long running times, often requiring many processor-core years of computation, AbcSmc is particularly well-suited to being used in high performance (e.g. cluster or supercomputer) environments. AbcSmc includes a convenient means of distributing and gathering work in HPC environments: the program pulls jobs from and writes output to a standardized SQL database, and implements a dynamic load balancing scheme to compensate for variable simulation run times and hardware failures. AbcSmc uses SQLite for the database, for portability of data.
Keywords
stochastic modelsItem Type | Dataset |
---|---|
Capture method | Other |
Date | 13 October 2023 |
Language(s) of written materials | English |
Creator(s) |
Pearson, CAB |
LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 29 Jul 2024 13:33 |
Last Modified | 29 Jul 2024 13:33 |
Publisher | Github |
Explore Further
- Github (Online Data Resource)