abc: Tools for Approximate Bayesian Computation (ABC). Implements several ABC algorithms for performing parameter estimation, model selection, and goodness-of-fit. Cross-validation tools are also available for measuring the accuracy of ABC estimates, and to calculate the misclassification probabilities of different models.
Keywords for this software
References in zbMATH (referenced in 8 articles )
Showing results 1 to 8 of 8.
- Duforet-Frebourg, Nicolas; Slatkin, Montgomery: Isolation-by-distance-and-time in a stepping-stone model (2016)
- Brand, Samuel P.C.; Tildesley, Michael J.; Keeling, Matthew J.: Rapid simulation of spatial epidemics: a spectral method (2015)
- Jabot, Franck: Why preferring parametric forecasting to nonparametric methods? (2015)
- Ross, Robert J.H.; Yates, C.A.; Baker, R.E.: Inference of cell-cell interactions from population density characteristics and cell trajectories on static and growing domains (2015)
- Blum, M.G.B.; Nunes, M.A.; Prangle, D.; Sisson, S.A.: A comparative review of dimension reduction methods in approximate Bayesian computation (2013)
- Marin, Jean-Michel; Pudlo, Pierre; Robert, Christian P.: Approximate Bayesian computational methods (2012)
- Peters, G.W.; Fan, Y.; Sisson, S.A.: On sequential Monte Carlo, partial rejection control and approximate Bayesian computation (2012)
- Mesterton-Gibbons, Mike; Gavrilets, Sergey; Gravner, Janko; Akçay, Erol: Models of coalition or alliance formation (2011)