Goodness of fit for models with intractable likelihood
Author
Abstract
Suggested Citation
DOI: 10.1007/s11749-020-00747-7
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- repec:dau:papers:123456789/555 is not listed on IDEAS
- D.A.S. Fraser & Judith Rousseau, 2008. "Studentization and deriving accurate p-values," Biometrika, Biometrika Trust, vol. 95(1), pages 1-16.
- Hjort, Nils Lid & Dahl, Fredrik A. & Steinbakk, Gunnhildur Hognadottir, 2006. "Post-Processing Posterior Predictive p Values," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1157-1174, September.
- Joel R. Norris & Robert J. Allen & Amato T. Evan & Mark D. Zelinka & Christopher W. O’Dell & Stephen A. Klein, 2016. "Evidence for climate change in the satellite cloud record," Nature, Nature, vol. 536(7614), pages 72-75, August.
- Paul Fearnhead & Dennis Prangle, 2012. "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(3), pages 419-474, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017.
"Bayesian estimation of agent-based models,"
Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
- Jakob Grazzini & Matteo Richiardi & Mike Tsionas, 2015. "Bayesian Estimation of Agent-Based Models," Economics Papers 2015-W12, Economics Group, Nuffield College, University of Oxford.
- Jakob Grazzini & Matteo G. Richiardi & Mike Tsionas, 2015. "Bayesian Estimation of Agent-Based Models," LABORatorio R. Revelli Working Papers Series 145, LABORatorio R. Revelli, Centre for Employment Studies.
- D.T. Frazier & G.M. Martin & C.P. Robert & J. Rousseau, 2016. "Asymptotic Properties of Approximate Bayesian Computation," Monash Econometrics and Business Statistics Working Papers 18/16, Monash University, Department of Econometrics and Business Statistics.
- Xing Ju Lee & Christopher C. Drovandi & Anthony N. Pettitt, 2015. "Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets," Biometrics, The International Biometric Society, vol. 71(1), pages 198-207, March.
- McKinley, Trevelyan J. & Ross, Joshua V. & Deardon, Rob & Cook, Alex R., 2014. "Simulation-based Bayesian inference for epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 434-447.
- Pierre-Olivier Goffard & Patrick Laub, 2021. "Approximate Bayesian Computations to fit and compare insurance loss models," Working Papers hal-02891046, HAL.
- Bertl Johanna & Ewing Gregory & Kosiol Carolin & Futschik Andreas, 2017. "Approximate maximum likelihood estimation for population genetic inference," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 291-312, December.
- Florian Maire & Nial Friel & Pierre ALQUIER, 2017. "Informed Sub-Sampling MCMC: Approximate Bayesian Inference for Large Datasets," Working Papers 2017-40, Center for Research in Economics and Statistics.
- Perepolkin, Dmytro & Goodrich, Benjamin & Sahlin, Ullrika, 2023. "The tenets of quantile-based inference in Bayesian models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
- Espen Bernton & Pierre E. Jacob & Mathieu Gerber & Christian P. Robert, 2019. "Approximate Bayesian computation with the Wasserstein distance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 235-269, April.
- Zhao, Guimei & Xu, Xingzhong, 2014. "The one-sided posterior predictive p-value for Fieller’s problem," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 57-62.
- Chkrebtii, Oksana A. & Cameron, Erin K. & Campbell, David A. & Bayne, Erin M., 2015. "Transdimensional approximate Bayesian computation for inference on invasive species models with latent variables of unknown dimension," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 97-110.
- Jonathan U Harrison & Ruth E Baker, 2018. "The impact of temporal sampling resolution on parameter inference for biological transport models," PLOS Computational Biology, Public Library of Science, vol. 14(6), pages 1-30, June.
- Baey, Charlotte & Smith, Henrik G. & Rundlöf, Maj & Olsson, Ola & Clough, Yann & Sahlin, Ullrika, 2023. "Calibration of a bumble bee foraging model using Approximate Bayesian Computation," Ecological Modelling, Elsevier, vol. 477(C).
- Gael M. Martin & Brendan P.M. McCabe & David T. Frazier & Worapree Maneesoonthorn & Christian P. Robert, 2016. "Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 09/16, Monash University, Department of Econometrics and Business Statistics.
- Alexander Buchholz & Nicolas CHOPIN, 2017. "Improving approximate Bayesian computation via quasi Monte Carlo," Working Papers 2017-37, Center for Research in Economics and Statistics.
- Christian P. Robert, 2013. "Bayesian Computational Tools," Working Papers 2013-45, Center for Research in Economics and Statistics.
- Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046, October.
- Buzbas, Erkan O. & Rosenberg, Noah A., 2015. "AABC: Approximate approximate Bayesian computation for inference in population-genetic models," Theoretical Population Biology, Elsevier, vol. 99(C), pages 31-42.
- Friedrich, Marina & Smeekes, Stephan & Urbain, Jean-Pierre, 2020.
"Autoregressive wild bootstrap inference for nonparametric trends,"
Journal of Econometrics, Elsevier, vol. 214(1), pages 81-109.
- Friedrich, Marina & Smeekes, Stephan & Urbain, Jean-Pierre, 2017. "Autoregressive Wild Bootstrap Inference for Nonparametric Trends," Research Memorandum 010, Maastricht University, Graduate School of Business and Economics (GSBE).
- Marina Friedrich & Stephan Smeekes & Jean-Pierre Urbain, 2018. "Autoregressive Wild Bootstrap Inference for Nonparametric Trends," Papers 1807.02357, arXiv.org, revised Nov 2019.
- C. Jessica E. Metcalf & David A. Stephens & Mark Rees & Svata M. Louda & Kathleen H. Keeler, 2009. "Using Bayesian inference to understand the allocation of resources between sexual and asexual reproduction," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 143-170, May.
More about this item
Keywords
Approximate Bayesian computation; Model adequacy; Model checking; Simulation-based modeling;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:30:y:2021:i:3:d:10.1007_s11749-020-00747-7. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.