Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data
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References listed on IDEAS
- C. C. Drovandi & A. N. Pettitt, 2011. "Estimation of Parameters for Macroparasite Population Evolution Using Approximate Bayesian Computation," Biometrics, The International Biometric Society, vol. 67(1), pages 225-233, March.
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Ryan, Elizabeth G. & Drovandi, Christopher C. & Thompson, M. Helen & Pettitt, Anthony N., 2014. "Towards Bayesian experimental design for nonlinear models that require a large number of sampling times," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 45-60.
- Abebe, Haftom T. & Tan, Frans E.S. & Van Breukelen, Gerard J.P. & Berger, Martijn P.F., 2014. "Bayesian D-optimal designs for the two parameter logistic mixed effects model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1066-1076.
- repec:eee:csdana:v:113:y:2017:i:c:p:207-225 is not listed on IDEAS
- Azriel, David, 2014. "Optimal sequential designs in phase I studies," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 288-297.
More about this item
KeywordsClinical trials; Generalised linear model; Generalised non-linear model; Sequential design; Sequential Monte Carlo; Target stimulus;
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