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Parameter Redundancy and Identifiability | Diana Cole - Taylor & Francis Inc


Parameter Redundancy and Identifiability | Diana Cole
801.6 Lei

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(17-11-2024)
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Statistical and mathematical models are defined by parameters that describe different characteristics of those models.
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..
Such a model is said to be Parameter redundant, or the parameters are described as non-identifiable.
For example, two parameters that only ever appear in the model as a product could not be estimated individually; only the product can be estimated.
Ideally it would be possible to find Parameter estimates for every Parameter in that model, but, in some cases, this is not possible.
Statistical and mathematical models are defined by parameters that describe different characteristics of those models


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