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design [2012/05/07 08:24]
matt
design [2017/09/20 19:05] (current)
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 >The simulation-based approach allows one to start the model-based optimization of experiments at an early stage of the parameter estimation process, in situations where the classical design criteria are not available... >The simulation-based approach allows one to start the model-based optimization of experiments at an early stage of the parameter estimation process, in situations where the classical design criteria are not available...
  
-Extends **Muller, P., Sanso, B., and De Iorio, M. (2004), “Optimal Bayesian Design by Inhomogeneous Markov Chain +Use the term "​Experimental Map" ​to refer to a distribution of designs.
-Simulation,​” Journal of the American Statistical Association,​ 99 (467), 788–798**. This is "​Bayesian simulation-based optimal design"​. +
- +
-Use the term "​Experimental Map".+
  
 <​code>​ <​code>​
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 } }
 </​code>​ </​code>​
 +
 +==== Further Reading ====
 +
 +=== Optimal Design ===
 +
 +**Han, C., and Chaloner, K. (2004), “Bayesian Experimental Design for Nonlinear Mixed-Effects Models With Application to HIV Dynamics,​” Biometrics, 60, 25–33.**
 +
 +**Muller, P., Sanso, B., and De Iorio, M. (2004), “Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation,​” Journal of the American Statistical Association,​ 99 (467), 788–798**. This is "​Bayesian simulation-based ptimal design"​.
 +
 +=== Differential Equations ===
 +
 +**Liang, H., and Wu, H. (2008), “Parameter Estimation for Differential Equation Models Using a Framework of Measurement Error in Regression Models,” Journal of the American Statistical Association,​ 103, 1570–1583.**
 +
 +**Ramsay, J. O., Hooker, G., Campbell, D., and Cao, J. (2007), “Parameter Estimation for Differential Equations: A Generalized Smoothing Approach” (with discussion),​ Journal of the Royal Statistical Society, Ser. B, 69, 741–796**
 +
design.txt · Last modified: 2017/09/20 19:05 (external edit)