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Update docs/src/inverse_problems/structural_identifiability.md
Co-authored-by: Sam Isaacson <[email protected]>
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docs/src/inverse_problems/structural_identifiability.md

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Catalyst contains a special extension for carrying out structural identifiability analysis using the [StructuralIdentifiability.jl](https://github.com/SciML/StructuralIdentifiability.jl) package. This enables StructuralIdentifiability's `assess_identifiability`, `assess_local_identifiability`, and `find_identifiable_functions` functions to be called directly on Catalyst `ReactionSystem`s. It also implements specialised routines to make these more efficient when applied to reaction network models. How to use these functions is described in the following tutorial, with [StructuralIdentifiability providing a more extensive documentation](https://docs.sciml.ai/StructuralIdentifiability/stable/).
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Structural identifiability can be divided into *local* and *global* identifiability. If a model quantity is locally identifiable, it means that its true value can be determined down to a finite-number of possible options. This also means that there is some limited region around the quantity's true value where this true value is the only possible value (and hence, within this region, the quantity is fully identifiable). Globally identifiable quantities' values, on the other hand, can be uniquely determined. Again, while identifiability can be confirmed structurally for a model, it does not necessarily mean that they are practically identifiable for some given data.
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Structural identifiability can be divided into *local* and *global* identifiability. If a model quantity is locally identifiable, it means that its true value can be determined down to a finite-number of possible options. This also means that there is some limited region around the quantity's true value where this true value is the only possible value (and hence, within this region, the quantity is fully identifiable). Globally identifiable quantities' values, on the other hand, can be uniquely determined. Again, while identifiability can be confirmed structurally for a quantity, it does not necessarily mean that it is practically identifiable for some given data.
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Generally, there are three types of quantities for which identifiability can be assessed.
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- Parameters (e.g. $p1$ and $p2$).

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