up

Author: TorkelE

docs/src/inverse_problems/structural_identifiability.md

@@ -22,7 +22,7 @@ StructuralIdentifiability currently assesses identifiability for the first two o
 
 ### Basic example
 
-Local identifiability can be assessed using the `assess_identifiability` function. For each model quantity (parameters and variables), it will assess whether they are:
+Global identifiability can be assessed using the `assess_identifiability` function. For each model quantity (parameters and variables), it will assess whether they are:
 - Globally identifiable.
 - Locally identifiable.
 - Unidentifiable.
@@ -94,7 +94,7 @@ assess_local_identifiability(goodwind_oscillator; measured_quantities=[:M], logl
 We note that the results are consistent with those produced by `assess_identifiability` (with globally or locally identifiable quantities here all being assessed as at least locally identifiable).
 
 ## Finding identifiable functions
-Finally, StructuralIdentifiability provides the `find_identifiable_functions` function. Rather than determining the identifiability of each parameter and initial condition of the model, it finds a minimal set of identifiable functions, such as any other identifiable expression of the model can be generated by these. Let us again consider the Goodwind oscillator, using the `find_identifiable_functions` function we find that identifiability can be reduced to five globally identifiable expressions:
+Finally, StructuralIdentifiability provides the `find_identifiable_functions` function. Rather than determining the identifiability of each parameter and state of the model, it finds a set of identifiable functions, such as any other identifiable expression of the model can be generated by these. Let us again consider the Goodwind oscillator, using the `find_identifiable_functions` function we find that identifiability can be reduced to five globally identifiable expressions:
 ```example si1
 find_identifiable_functions(goodwind_oscillator; measured_quantities=[:M], loglevel=Logging.Error)
 ```