In mathematics, a vector measure is a function defined on a family of sets and taking vector values satisfying certain properties. It is a generalization of the concept of finite measure, which takes nonnegative real values only.
Given a field of sets and a Banach space a finitely additive vector measure (or measure, for short) is a function such that for any two disjoint sets and in one has
A vector measure is called countably additive if for any sequence of disjoint sets in such that their union is in it holds that
with the series on the right-hand side convergent in the norm of the Banach space
It can be proved that an additive vector measure is countably additive if and only if for any sequence as above one has
where is the norm on
Countably additive vector measures defined on sigma-algebras are more general than finite measures, finite signed measures, and complex measures, which are countably additive functions taking values respectively on the real interval the set of real numbers, and the set of complex numbers.
Consider the field of sets made up of the interval together with the family of all Lebesgue measurable sets contained in this interval. For any such set define
where is the indicator function of Depending on where is declared to take values, two different outcomes are observed.
viewed as a function from to the -space is a vector measure which is not countably-additive.
viewed as a function from to the -space is a countably-additive vector measure.
Both of these statements follow quite easily from the criterion () stated above.
Given a vector measure the variation of is defined as
where the supremum is taken over all the partitions
of into a finite number of disjoint sets, for all in Here, is the norm on
The variation of is a finitely additive function taking values in It holds that
for any in If is finite, the measure is said to be of bounded variation. One can prove that if is a vector measure of bounded variation, then is countably additive if and only if is countably additive.
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The course is based on Durrett's text book
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In mathematics, especially measure theory, a set function is a function whose domain is a family of subsets of some given set and that (usually) takes its values in the extended real number line which consists of the real numbers and A set function generally aims to subsets in some way. Measures are typical examples of "measuring" set functions. Therefore, the term "set function" is often used for avoiding confusion between the mathematical meaning of "measure" and its common language meaning.
In mathematics, signed measure is a generalization of the concept of (positive) measure by allowing the set function to take negative values. There are two slightly different concepts of a signed measure, depending on whether or not one allows it to take infinite values. Signed measures are usually only allowed to take finite real values, while some textbooks allow them to take infinite values. To avoid confusion, this article will call these two cases "finite signed measures" and "extended signed measures".
In mathematics, the concept of a measure is a generalization and formalization of geometrical measures (length, area, volume) and other common notions, such as magnitude, mass, and probability of events. These seemingly distinct concepts have many similarities and can often be treated together in a single mathematical context. Measures are foundational in probability theory, integration theory, and can be generalized to assume negative values, as with electrical charge.
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ISTE Wiley2023
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