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In [[measure theory]], a '''continuity set''' of a [[measure (mathematics)|measure]] ''μ'' is any [[Borel set]] ''B'' such that
: <math>
    \mu(\partial B) = 0\,.
  </math>


where <math>\partial B</math> is the [[boundary set]] of ''B''.  For [[signed measure]]s, one asks that
: <math>
    |\mu|(\partial B) = 0\,.
  </math>


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The class of all continuity sets for given measure ''μ'' forms a [[Ring_of_sets|ring]].<ref>Cuppens, R. (1975) Decomposition of multivariate probability. Academic Press, New York.</ref>
 
Similarly, for a random variable ''X'' a set ''B'' is called '''continuity set''' if
: <math>
    \Pr[X \in \partial B] = 0,
  </math>
otherwise ''B'' is called the ''discontinuity set''. The collection of all discontinuity sets is [[sparse set|sparse]]. In particular, given any collection of sets {''B<sub>α</sub>''} with pairwise disjoint boundaries, all but at most countably many of them will be the continuity sets.<ref>van der Vaart (1998) Asymptotic statistics. Cambridge University Press. ISBN 978-0-521-78450-4. Page 7</ref>
 
The '''continuity set''' ''C''(''f'') of a function ''f'' is the set of points where ''f'' is continuous.
 
== References ==
{{reflist}}
 
[[Category:Measure theory]]
 
{{mathanalysis-stub}}

Revision as of 04:26, 22 January 2014

In measure theory, a continuity set of a measure μ is any Borel set B such that

where is the boundary set of B. For signed measures, one asks that

The class of all continuity sets for given measure μ forms a ring.[1]

Similarly, for a random variable X a set B is called continuity set if

otherwise B is called the discontinuity set. The collection of all discontinuity sets is sparse. In particular, given any collection of sets {Bα} with pairwise disjoint boundaries, all but at most countably many of them will be the continuity sets.[2]

The continuity set C(f) of a function f is the set of points where f is continuous.

References

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Template:Mathanalysis-stub

  1. Cuppens, R. (1975) Decomposition of multivariate probability. Academic Press, New York.
  2. van der Vaart (1998) Asymptotic statistics. Cambridge University Press. ISBN 978-0-521-78450-4. Page 7