Linked from

The 25 pages that link to Indicator function, each with the reason it gives.

• Cumulative distribution functionRelated: The event that a variable is at most a threshold can be represented by an indicator.

• Inclusion–exclusion principleRelated: Summing indicators turns union counting into a pointwise alternating-sum identity.

• Event (probability theory)Related: It encodes an event as a random variable whose expectation equals its probability.

• Fubini's theoremRelated: Integrating indicators connects Fubini's theorem to product measures of measurable sets.

• Measurable functionRelated: Its measurability is equivalent to measurability of the set it marks.

• Markov's inequalityRelated: An indicator of the threshold event turns its probability into an expectation.

• MultisetRelated: A multiset generalizes membership indicators by allowing integer-valued counts.

• Empirical distribution functionRelated: Averaging indicators of observations below a threshold gives the empirical function’s formula.

• Piecewise functionRelated: It encodes region-based rules using sets and can build many piecewise functions.

• Partition of a setRelated: Indicators can encode whether each element belongs to a given block.

• Sign functionRelated: The sign function can be expressed using indicators of the positive and negative half-lines.

• Support functionRelated: Taking its convex conjugate produces the set’s support function.

• Law of total probabilityRelated: Indicators turn event probabilities into expectations, where the partition identity generalizes.

• Law of total expectationRelated: Indicators turn event probabilities into expectations that can be decomposed by cases.

• Lebesgue density theoremRelated: Its averages over balls are exactly the set's local proportions.

• Bonferroni inequalitiesRelated: Pointwise bounds on indicators of unions provide a route to Bonferroni inequalities.

• Rectangular functionRelated: A rectangular pulse is a scaled indicator of an interval.

• Basu's theoremRelated: Applying completeness to conditional event probabilities yields the independence conclusion.

• Steinhaus theoremRelated: Its convolution with a reflected indicator encodes the measure of translated intersections.

• Boole's inequalityRelated: Event indicators turn a union into a pointwise inequality whose expectation proves the bound.

• Steffensen's inequalityRelated: Endpoint interval indicators realize the extreme weights behind the inequality.