Intensity Measure
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In
probability theory Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expre ...
, an intensity measure is a measure that is derived from a
random measure In probability theory, a random measure is a measure-valued random element. Random measures are for example used in the theory of random processes, where they form many important point processes such as Poisson point processes and Cox processes. ...
. The intensity measure is a non-random measure and is defined as the
expectation value In probability theory, the expected value (also called expectation, expectancy, expectation operator, mathematical expectation, mean, expectation value, or first moment) is a generalization of the weighted average. Informally, the expected va ...
of the random measure of a set, hence it corresponds to the average volume the random measure assigns to a set. The intensity measure contains important information about the properties of the random measure. A
Poisson point process In probability theory, statistics and related fields, a Poisson point process (also known as: Poisson random measure, Poisson random point field and Poisson point field) is a type of mathematical object that consists of points randomly located ...
, interpreted as a random measure, is for example uniquely determined by its intensity measure.


Definition

Let \zeta be a
random measure In probability theory, a random measure is a measure-valued random element. Random measures are for example used in the theory of random processes, where they form many important point processes such as Poisson point processes and Cox processes. ...
on the
measurable space In mathematics, a measurable space or Borel space is a basic object in measure theory. It consists of a set and a σ-algebra, which defines the subsets that will be measured. It captures and generalises intuitive notions such as length, area, an ...
(S, \mathcal A) and denote the
expected value In probability theory, the expected value (also called expectation, expectancy, expectation operator, mathematical expectation, mean, expectation value, or first Moment (mathematics), moment) is a generalization of the weighted average. Informa ...
of a random element Y with \operatorname E . The intensity measure : \operatorname E \zeta \colon \mathcal A \to ,\infty of \zeta is defined as : \operatorname E \zeta(A)= \operatorname E zeta(A) for all A \in \mathcal A. Note the difference in notation between the expectation value of a random element Y , denoted by \operatorname E and the intensity measure of the random measure \zeta , denoted by \operatorname E\zeta .


Properties

The intensity measure \operatorname E\zeta is always s-finite and satisfies :\operatorname E \left \int f(x) \; \zeta(\mathrm dx)\right \int f(x) \operatorname E\zeta(dx) for every positive
measurable function In mathematics, and in particular measure theory, a measurable function is a function between the underlying sets of two measurable spaces that preserves the structure of the spaces: the preimage of any measurable set is measurable. This is in ...
f on (S, \mathcal A) .


References

{{Measure theory Measures (measure theory) Probability theory