Parameter Redundancy and Identifiability - Cole, Diana

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Résumé :
1. Introduction 2. Problems With Parameter Redundancy 3. Parameter Redundancy and Identifiability Definitions and Theory 4. Practical General Methods for Detecting Parameter Redundancy and Identifiability 5. Detecting Parameter Redundancy and Identifiability in Complex Models 6. Bayesian Identifiability 7. Identifiability in Continuous State-Space Models 8. Identifiability in Discrete State-Space Models 9. Detecting Parameter Redundancy in Ecological Models 10. Concluding Remarks Appendix A. Maple Code Appendix B. Winbugs and R Code...

Biographie:
only the product can be estimated. Such a model is said to be parameter redundant, or the parameters are described as non-identifiable. This book explains why parameter redundancy and non-identifiability is a problem and the different methods that can be used for detection, including in a Bayesian context.

Key features of this book:

• Detailed discussion of the problems caused by parameter redundancy and non-identifiability
• Explanation of the different general methods for detecting parameter redundancy and non-identifiability, including symbolic algebra and numerical methods
• Chapter on Bayesian identifiability
• Throughout illustrative examples are used to clearly demonstrate each problem and method. Maple and R code are available for these examples
• More in-depth focus on the areas of discrete and continuous state-space models and ecological statistics, including methods that have been specifically developed for each of these areas

This book is designed to make parameter redundancy and non-identifiability accessible and understandable to a wide audience from masters and PhD students to researchers, from mathematicians and statisticians to practitioners using mathematical or statistical models.