Discrete Statistical Model

References

(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.