abctools

R package abctools: Tools for ABC Analyses. Tools for approximate Bayesian computation including summary statistic selection and assessing coverage.

Keywords for this software

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References in zbMATH (referenced in 8 articles )

Showing results 1 to 8 of 8.
Sorted by year (citations)

  1. Ke, Yuqin; Tian, Tianhai: Approximate Bayesian computational methods for the inference of unknown parameters (2019)
  2. Martin, Gael M.; McCabe, Brendan P. M.; Frazier, David T.; Maneesoonthorn, Worapree; Robert, Christian P.: Auxiliary likelihood-based approximate Bayesian computation in state space models (2019)
  3. Ariella L.Gladstein; Consuelo D. Quinto-Cortés; Julian L. Pistorius; David Christy; Logan Gantner; Blake L. Joyce: SimPrily: A Python framework to simplify high-throughput genomic simulations (2018) not zbMATH
  4. Bee, M.; Trapin, L.: A characteristic function-based approach to approximate maximum likelihood estimation (2018)
  5. Karabatsos, George; Leisen, Fabrizio: An approximate likelihood perspective on ABC methods (2018)
  6. Rodrigues, G. S.; Prangle, D.; Sisson, S. A.: Recalibration: a post-processing method for approximate Bayesian computation (2018)
  7. Prangle, D.; Blum, M. G. B.; Popovic, G.; Sisson, S. A.: Diagnostic tools for approximate Bayesian computation using the coverage property (2014)
  8. Blum, M. G. B.; Nunes, M. A.; Prangle, D.; Sisson, S. A.: A comparative review of dimension reduction methods in approximate Bayesian computation (2013)