Measures: Difference between revisions

From Optimal Transport Wiki
Jump to navigation Jump to search
No edit summary
No edit summary
Line 6: Line 6:
# <math>\mu\left(\emptyset\right) = 0</math>,
# <math>\mu\left(\emptyset\right) = 0</math>,
# Let <math>\left\{E_k\right\}_{k = 1}^{\infty}</math> be a disjoint sequence of sets such that each <math>E_k \in \mathcal{M}</math>. Then, <math>\mu\left(\cup_{k = 1}^{\infty} E_k\right) = \sum_{k = 1}^{\infty} \mu\left(E_k\right)</math>.
# Let <math>\left\{E_k\right\}_{k = 1}^{\infty}</math> be a disjoint sequence of sets such that each <math>E_k \in \mathcal{M}</math>. Then, <math>\mu\left(\cup_{k = 1}^{\infty} E_k\right) = \sum_{k = 1}^{\infty} \mu\left(E_k\right)</math>.
If the previous conditions are satisfied, the structure <math>\left(X, \mathcal{M}, \mu\right)</math> is called a '''measure space'''.


==Properties==
==Properties==
 
Let <math>\left(X, \mathcal{M}, \mu\right)</math> be a measure space.
# '''Countable Additivity:''' Let <math>\left\{E_k\right\}_{k = 1}^{n}</math> be a finite disjoint sequence of sets such that each <math>E_k \in \mathcal{M}</math>. Then, <math>\mu\left(\cup_{k = 1}^{n} E_k\right) = \sum_{k = 1}^{n} \mu\left(E_k\right)</math>. This follows directly from the defintion of measures by taking <math>E_{n+1} = E_{n+2} = ... = \emptyset</math>.
# '''Countable Additivity:''' Let <math>\left\{E_k\right\}_{k = 1}^{n}</math> be a finite disjoint sequence of sets such that each <math>E_k \in \mathcal{M}</math>. Then, <math>\mu\left(\cup_{k = 1}^{n} E_k\right) = \sum_{k = 1}^{n} \mu\left(E_k\right)</math>. This follows directly from the defintion of measures by taking <math>E_{n+1} = E_{n+2} = ... = \emptyset</math>.
# '''Monotonicity:''' Let <math>E, F \in \mathcal{M}</math> such that <math>E \subseteq F</math>. Then, <math>\mu\left(E\right) \leq \mu\left(F\right)</math>.
# '''Subadditivity:''' Let <math>\left\{E_k\right\}_{k = 1}^{\infty} \subseteq \mathcal{M}</math>. Then, <math>\mu\left(\cup_{k = 1}^{\infty} E_k\right) \leq \sum_{k = 1}^{\infty} \mu\left(E_k\right)</math>.
# '''Continuity from Below:''' Let <math>\left\{E_k\right\}_{k = 1}^{\infty} \subseteq \mathcal{M}</math> such that <math>E_1 \subseteq E_2 \subseteq ...</math>. Then, <math>\mu\left(\cup_{k = 1}^{\infty} E_k\right) = \lim_{k \rightarrow \infty} \mu\left(E_k\right)</math>.
# '''Continuity from Above:''' Let <math>\left\{E_k\right\}_{k = 1}^{\infty} \subseteq \mathcal{M}</math> such that <math>E_1 \supseteq E_2 \supseteq ...</math> and <math>\mu\left(E_1\right) < \infty</math>. Then, <math>\mu\left(\cap_{k = 1}^{\infty} E_k\right) = \lim_{k \rightarrow \infty} \mu\left(E_k\right)</math>.


==Examples==
==Examples==

Revision as of 04:27, 17 December 2020

This page is under construction.

Definition

Let be a set equipped with a -algebra . A measure on (also referred to simply as measure on if is understood) is a function that satisfies the following criteria:

  1. ,
  2. Let be a disjoint sequence of sets such that each . Then, .

If the previous conditions are satisfied, the structure is called a measure space.

Properties

Let be a measure space.

  1. Countable Additivity: Let be a finite disjoint sequence of sets such that each . Then, . This follows directly from the defintion of measures by taking .
  2. Monotonicity: Let such that . Then, .
  3. Subadditivity: Let . Then, .
  4. Continuity from Below: Let such that . Then, .
  5. Continuity from Above: Let such that and . Then, .

Examples

.

References

.