Identifiability

In statistics, identifiability is a property which a model must satisfy for precise inference to be possible. A model is identifiable if it is theoretically possible to learn the true values of this model's underlying parameters after obtaining an infinite number of observations from it. Mathematically, this is equivalent to saying that different values of the parameters must generate different probability distributions of the observable variables. Usually the model is identifiable only under certain technical restrictions, in which case the set of these requirements is called the identification conditions.

Identifiability - Wikipedia Jump to content From Wikipedia, the free encyclopedia Statistical property which a model must satisfy to allow precise inference For the related problem in economics, see Parameter identification problem . For the concept of identifiability in the area of system identification, see Structural identifiability . In statistics , identifiability is a property which a model must satisfy for precise inference to be possible. A model is identifiable if it is theoretically possible to learn the true values of this model's underlying parameters after obtaining an infinite nu

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