abc
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 37 articles )
Showing results 1 to 20 of 37.
Sorted by year (- Jhwueng, Dwueng-Chwuan: Modeling rate of adaptive trait evolution using Cox-Ingersoll-Ross process: an approximate Bayesian computation approach (2020)
- Thong, David; Streftaris, George; Gibson, Gavin J.: Latent likelihood ratio tests for assessing spatial kernels in epidemic models (2020)
- Griswold, Cortland K.: An ancestral process with selection in an ecological community (2019)
- Ke, Yuqin; Tian, Tianhai: Approximate Bayesian computational methods for the inference of unknown parameters (2019)
- Kobayashi, Genya; Kakamu, Kazuhiko: Approximate Bayesian computation for Lorenz curves from grouped data (2019)
- Koblents, Eugenia; Mariño, Inés P.; Míguez, Joaquín: Bayesian computation methods for inference in stochastic kinetic models (2019)
- Lee, Jeong Eun; Nicholls, Geoff K.; Ryder, Robin J.: Calibration procedures for approximate Bayesian credible sets (2019)
- Maire, Florian; Friel, Nial; Alquier, Pierre: Informed sub-sampling MCMC: approximate Bayesian inference for large datasets (2019)
- Ziwen An, Leah F. South, Christopher C. Drovand: BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood (2019) arXiv
- Ho, Lam Si Tung; Crawford, Forrest W.; Suchard, Marc A.: Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease (2018)
- Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W.; Minin, Vladimir N.; Suchard, Marc A.: Birth/birth-death processes and their computable transition probabilities with biological applications (2018)
- Karabatsos, George; Leisen, Fabrizio: An approximate likelihood perspective on ABC methods (2018)
- Lambert, Ben; MacLean, Adam L.; Fletcher, Alexander G.; Combes, Alexander N.; Little, Melissa H.; Byrne, Helen M.: Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis (2018)
- McKinley, Trevelyan J.; Vernon, Ian; Andrianakis, Ioannis; McCreesh, Nicky; Oakley, Jeremy E.; Nsubuga, Rebecca N.; Goldstein, Michael; White, Richard G.: Approximate Bayesian computation and simulation-based inference for complex stochastic epidemic models (2018)
- Nott, David J.; Drovandi, Christopher C.; Mengersen, Kerrie; Evans, Michael: Approximation of Bayesian predictive (p)-values with regression ABC (2018)
- Skvortsov, Alex; Ristic, Branko; Kamenev, Alex: Predicting population extinction from early observations of the Lotka-Volterra system (2018)
- Spantini, Alessio; Bigoni, Daniele; Marzouk, Youssef: Inference via low-dimensional couplings (2018)
- Dennis Prangle: gk: An R Package for the g-and-k and generalised g-and-h Distributions (2017) arXiv
- Geppert, Leo N.; Ickstadt, Katja; Munteanu, Alexander; Quedenfeld, Jens; Sohler, Christian: Random projections for Bayesian regression (2017)
- Guha, Nilabja; Tan, Xiaosi: Multilevel approximate Bayesian approaches for flows in highly heterogeneous porous media and their applications (2017)