A parametric model is a collection of probability distributions such that each member of this collection, Pθ, is described by a finite-dimensional parameter θ. The set of all allowable values for the parameter is denoted Θ ⊆ Rk, and the model itself is written as
When the model consists of absolutely continuous distributions, it is often specified in terms of corresponding probability density functions:
The parametric model is called identifiable if the mapping θ ↦ Pθ is invertible, that is there are no two different parameter values θ1 and θ2 such that Pθ1 = Pθ2.
Read more about Parametric Model: Regular Parametric Model, See Also
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