# The Radon-Nikodym Theorem

• Jean Jacod
• Philip Protter
Part of the Universitext book series (UTX)

## Abstract

Let (ω, F, P) be a probability space. Suppose a random variable X ≥ 0 a.s. has the property E{X| = 1. Then if we define a set function Q on F by
$$Q\left( \wedge \right) = E\left\{ {1_ \wedge X} \right\}$$
(28.1)
then it is easy to see that Q defines a new probability (see Exercise 9.5). Indeed
$$Q\left( \Omega \right) = E\left\{ {1_\Omega X} \right\} = E\left\{ X \right\} = 1$$
and A1, A2, A3, … are disjoint in F then
$$\begin{gathered} Q\left( {\bigcup\limits_{i = 1}^\infty {A_i } } \right) = E\{ 1_{ \cup _{i = 1}^\infty A_i } X\} \hfill \\ = E\left\{ {\sum\limits_{i = 1}^\infty {1_{A_i } X} } \right\} \hfill \\ = \sum\limits_{i = 1}^\infty {E\{ 1_{A_i } ,X\} } \hfill \\ = \sum\limits_{i = 1}^\infty {Q(A_i )} \hfill \\ \end{gathered}$$
and we have countable additivity. The interchange of the expectation and the summation is justified by the Monotone Convergence Theorem (Theorem 9.1(d)).

## Keywords

Conditional Expectation Positive Random Variable Monotone Convergence Theorem Countable Additivity Hilbert Space Theory
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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