Optimizing Conditional Expectation

Click For Summary

Discussion Overview

The discussion revolves around the optimization of conditional expectation, specifically focusing on maximizing E(X|s) for a random variable X with an infinite sample space S. Participants explore theoretical frameworks and potential mathematical approaches related to this concept.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant suggests that without knowledge of X or S, a general strategy for maximizing E(X|s) may not exist, as different expectation values could be independent.
  • Another participant proposes viewing the problem as an infinite-dimensional variant of Factor Analysis or PCA, suggesting the use of functional-analytic techniques related to infinite-dimensional linear operators.
  • A later reply questions the definition of S, asking whether it refers to the values X can take or the probability space, and argues that conditioning on a specific outcome s fixes the value of X, leading to a different interpretation of the problem.

Areas of Agreement / Disagreement

Participants express differing views on the nature of S and the implications for maximizing conditional expectation. There is no consensus on a general strategy or approach, and the discussion remains unresolved.

Contextual Notes

Participants highlight the dependence on definitions and the potential complexity introduced by the infinite-dimensional nature of the problem, which may affect the applicability of certain mathematical techniques.

WWGD
Science Advisor
Homework Helper
Messages
7,806
Reaction score
13,120
Hi all,
Let X be a random EDIT variable with (infinite) sample space S. Are there some results dealing with how to maximize

E(X|s ) (conditional expectation of X given s ) for s in S ?

Thanks.
 
Last edited:
Physics news on Phys.org
If you know nothing about X or S, I don't see how a general strategy would work. The different expectation values can be completely independent.
If you know something about X or S, there can be nice ways to find the optimal s.
 
Couldn't we see this as a sort of an infinite-dimensional variant of Factor Analysis/ PCA (where the elements of S are the infinite factors)? EDIT : Maybe we can use some functional-analytic techniques dealing with infinite-dimensional linear operators? I know there are generalizations to the infinite-dimensional case of , e.g., determinants, maybe there are generalizations of other aspects?
 
Last edited:
WWGD said:
Hi all,
Let X be a random EDIT variable with (infinite) sample space S. Are there some results dealing with how to maximize

E(X|s ) (conditional expectation of X given s ) for s in S ?

Thanks.
What is S supposed to be: the set of values which the random variable X can take, or the probability space on which it is defined?

In the latter case, X is a function from S to the real numbers R. When you condition on a particular outcome s in S, you fix the value of X; it's X(s). According to any sensible definition of conditional expectation, we should take E(X | s) to be X(s).

And now you want to find the maximal value which this can be? This is no longer a probability question.
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 3 ·
Replies
3
Views
892
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K