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.
Alternative Title
AbcSmc
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 |
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