In the mathematical theory of probability and measure, a sub-probability measure is a measure that is closely related to probability measures. While probability measures always assign the value 1 to the underlying set, sub-probability measures assign a value lesser than or equal to 1 to the underlying set.

Definition

Let μ {\displaystyle \mu } be a measure on the measurable space ( X , A ) {\displaystyle (X,{\mathcal {A}})} .

Then μ {\displaystyle \mu } is called a sub-probability measure if μ ( X ) 1 {\displaystyle \mu (X)\leq 1} .

Properties

In measure theory, the following implications hold between measures: probability sub-probability finite σ -finite {\displaystyle {\text{probability}}\implies {\text{sub-probability}}\implies {\text{finite}}\implies \sigma {\text{-finite}}}

So every probability measure is a sub-probability measure, but the converse is not true. Also every sub-probability measure is a finite measure and a σ-finite measure, but the converse is again not true.

See also

  • Helly's selection theorem
  • Helly–Bray theorem

References


The probability distribution for the subcritical case () from the

Subjective probability primer prior probability

What is the submeasure competition about RPO 1.6.2. Source research

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