This shows you the differences between two versions of the page.
design [2012/05/07 08:24] matt |
design [2017/09/20 19:05] |
||
---|---|---|---|
Line 1: | Line 1: | ||
- | ====== Optimal Design of Experiments ====== | ||
- | ===== Literature ===== | ||
- | |||
- | **//Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations//**\\ | ||
- | **Cao, Jiguo and Huang, Jianhua Z. and Wu, Hulin**\\ | ||
- | |||
- | Some quotes: | ||
- | |||
- | > Classical optimal design criteria suffer from two major flaws when applied to nonlinear problems. First, they are based on linearizing the model around a point estimate of the unknown parameter and therefore depend on the uncertain value of that parameter. Second, classical design methods are unavailable in ill-posed estimation situations, where previous data lack the information needed to properly construct the design criteria... | ||
- | |||
- | >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 | ||
- | Simulation,” Journal of the American Statistical Association, 99 (467), 788–798**. This is "Bayesian simulation-based optimal design". | ||
- | |||
- | Use the term "Experimental Map". | ||
- | |||
- | <code> | ||
- | @article{doi:10.1198/jcgs.2011.10021, | ||
- | author = {Cao, Jiguo and Huang, Jianhua Z. and Wu, Hulin}, | ||
- | title = {Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations}, | ||
- | journal = {Journal of Computational and Graphical Statistics}, | ||
- | volume = {21}, | ||
- | number = {1}, | ||
- | pages = {42-56}, | ||
- | year = {2012}, | ||
- | doi = {10.1198/jcgs.2011.10021}, | ||
- | URL = {http://amstat.tandfonline.com/doi/abs/10.1198/jcgs.2011.10021}, | ||
- | eprint = {http://amstat.tandfonline.com/doi/pdf/10.1198/jcgs.2011.10021} | ||
- | } | ||
- | </code> |