Standard Statistical Model

A Standard Statistical Model is a Statistical Model that is either a Discrete Statistical Model or a Continuous Statistical Model.

• See: Probability Function.

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References

2008

• (Georgii, 2008) ⇒ Hans-Otto Georgii. (2008). “Stochastics: introduction to probability theory and statistics." Walter de Gruyter. ISBN:3110191458,
  • (a) A statistical model [math]\displaystyle{ M }[/math] = (X [math]\displaystyle{ F }[/math], P_v : [math]\displaystyle{ v }[/math] ∈ ϴ) is called a parametric model if ϴ ⊂ R^d for some [math]\displaystyle{ d }[/math] ∈ N. For [math]\displaystyle{ d }[/math]=1, [math]\displaystyle{ M }[/math] is called a one-parameter model.
  • (b) [math]\displaystyle{ M }[/math] is called a discrete model if [math]\displaystyle{ X }[/math] is discrete (i.e. at most countable), and ... [math]\displaystyle{ M }[/math] is called a continuous model iff [math]\displaystyle{ X }[/math] is a Borel subset of ... If either of these two cases applies, we say that [math]\displaystyle{ M }[/math] is a standard model.

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