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Contiguity (probability theory)

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In probability theory, two sequences of probability measures are said to be contiguous if asymptotically they share the same support. Thus the notion of contiguity extends the concept of absolute continuity to the sequences of measures.

The concept was originally introduced by Lucien Le Cam in the 1960s as part of his contribution to the development of abstract general asymptotic theory in mathematical statistics. Le Cam was instrumental during the period in the development of abstract general asymptotic theory in mathematical statistics. He is best known for the general concepts of local asymptotic normality and contiguity.

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Definition

Let (Ωn, Fn) be a sequence of measurable spaces, each equipped with two probability measures Pn and Qn. Then Qn is said to be contiguous with respect to Pn (denoted QnPn) if Pn(An) → 0 implies Qn(An) → 0 for every sequence of measurable sets An. The sequences Pn and Qn are said to be mutually contiguous or bi-contiguous (denoted Qn ◁▷ Pn) if both Qn is contiguous with respect to Pn and Pn is contiguous with respect to Qn. [2]

Applications

See also

External References

Notes

  1. ^ Wolfowitz J.(1974) Review of the book: "Contiguity of Probability Measures: Some Applications in Statistics. by George G. Roussas", Journal of the American Statistical Association, 69, 278–279 jstor
  2. ^ van der Vaart (1998, p. 87)
  3. ^ http://www.samsi.info/200506/fmse/course-info/werker-updated-nov14.pdf

References

  • van der Vaart, A. W. (1998). Asymptotic Statistics. Cambridge University Press. {{cite book}}: Cite has empty unknown parameter: |1= (help)CS1 maint: ref duplicates default (link)