Conditional expectation of three exponential distributed r.v.

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Discussion Overview

The discussion revolves around calculating the conditional expectation E[B | A < B < C] where A, B, and C are independent exponential random variables with different parameters. Participants explore various approaches to derive this expectation, including integral formulations and the application of conditional probability definitions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant expresses difficulty in calculating E[B | A < B < C] and mentions encountering complex integrals.
  • Another participant suggests that assuming independence of A, B, and C may simplify the problem.
  • A proposed method involves using the law of total expectation and calculating E[B | A < B < C, A = a] through integrals over the joint distribution.
  • Concerns are raised regarding the validity of the marginal distributions being exponential in the context of conditional expectations.
  • Participants discuss alternative formulations, including the ratio of integrals for E[B.I(A
  • One participant acknowledges a misunderstanding in their earlier reasoning and agrees with a correction regarding the marginal distributions.
  • A later reply simplifies the integral expression to a form involving the joint density over the region where A < B < C.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the best approach to calculate the conditional expectation, with multiple competing methods and some uncertainty about the validity of certain assumptions.

Contextual Notes

Some participants express uncertainty about the tractability of the integrals involved and the implications of independence on the marginal distributions. There are also unresolved questions about the correctness of specific steps in the calculations.

Ego7894612
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I've been struggling with this problem for more than 4 days now:

Let A, B and C be exponential distributed random variables with parameters lambda_A, lambda_B and lambda_C, respectively.

Calculate E [ B | A < B < C ] in terms of the lambda's.

I always seem get an integral which is impossible to calculate...

Who has a suggestion how to solve this problem?
 
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Ego7894612 said:
I always seem get an integral which is impossible to calculate...

That's how I'd try to do it too, can you show us what you got and where you were stuck?
 
First a remark: we may assume that A, B and C are independent random variables (this may help a lot).

[tex] E [ B | A < B < C ] = \int_{0}^\infty E [ B \, | \, A < B < C, A = a ] \; f_{A} ( a ) \; da [/tex]
[tex] = \int_{0}^\infty \int_{0}^\infty E [ B \, | \, A < B < C, A = a, C=c ] \; f_{A} ( a ) \; f_{C} ( c ) \; da \; dc.[/tex]
(Along with all that follows, this integral is only to be considered over R_+^2 and for c>a.)
[tex] = \int_{0}^\infty \int_{0}^\infty E [ B \, | \, a < B < c, A = a, C=c ] \; f_{A} ( a ) \; f_{C} ( c ) \; da \; dc[/tex]
(by independence)
[tex] = \int_{0}^\infty \int_{0}^\infty E [ B \, | \, a < B < c ] \; f_{A} ( a ) \; f_{C} ( c ) \; da \; dc[/tex]

We want to compute [tex]E [ B \, | \, a < B < c ].[/tex]

First note that
[tex]E [ B \, | \, a < B < c ] = \frac{ \int_a^c t f_{B} (t) dt }{P( B \in [a,c])}.[/tex]

We have[tex]\int_a^c t f_{B} (t) dt = ... = (a e^{- \lambda_B a} - c e^{- \lambda_B c}) + \frac{1}{\lambda_B} ( e^{- \lambda_B a} - e^{- \lambda_B c} )[/tex]
and
[tex]P(B \in [a,c]) = F_B (c) - F_B (a) = ... = e^{- \lambda_B a} - e^{- \lambda_B c}.[/tex]

Hence
[tex]E [ B \, | \, a < B < c ] = \frac{ (a e^{- \lambda_B a} - c e^{- \lambda_B c}) + \frac{1}{\lambda_B} ( e^{- \lambda_B a} - e^{- \lambda_B c} ) }{e^{- \lambda_B a} - e^{- \lambda_B c}},[/tex]
[tex]E [ B \, | \, a < B < c ] = \frac{ a e^{- \lambda_B a} - c e^{- \lambda_B c} }{e^{- \lambda_B a} - e^{- \lambda_B c}} + \frac{1}{\lambda_B}.[/tex]

So
[tex] E [ B | A < B < C ] = \int_{0}^\infty \int_{0}^\infty \left( \frac{ a e^{- \lambda_B a} - c e^{- \lambda_B c} }{e^{- \lambda_B a} - e^{- \lambda_B c}} + \frac{1}{\lambda_B} \right) \; f_{A} ( a ) \; f_{C} ( c ) \; da \; dc[/tex]
[tex] = \int_{0}^\infty \int_{0}^\infty \left( \frac{ a e^{- \lambda_B a} - c e^{- \lambda_B c} }{e^{- \lambda_B a} - e^{- \lambda_B c}} \right) \lambda_A e^{- \lambda_A a} \; \lambda_C e^{- \lambda_C c} \; da \; dc + [/tex]
[tex] \int_{0}^\infty \int_{0}^\infty \frac{1}{\lambda_B} \lambda_A e^{- \lambda_A a} \; \lambda_C e^{- \lambda_C c} \; da \; dc[/tex]Here's my problem: I can't compute the first of these integrals... And even then I'm not sure if what I'm doing here is correct... Is my calculation right, or is it wrong!? Is there perhaps a better way to calculate this? Etc.
 
Last edited:
Ego7894612 said:
[tex] E [ B | A < B < C ] = \int_{0}^\infty E [ B \, | \, A < B < C, A = a ] \; f_{A} ( a ) \; da [/tex]

I'm not sure about this line - the marginals of the conditional distribution aren't necessarily exponential. Another approach is to apply directly the definition of conditional probabilities, so that

[tex]E[B|A<B<C] = E[B.I(A<B<C)]/P[A<B<C][/tex]

which is a ratio of integrals that should both be tractable.

Hope this helps.
 
bpet said:
I'm not sure about this line - the marginals of the conditional distribution aren't necessarily exponential. Another approach is to apply directly the definition of conditional probabilities, so that

[tex]E[B|A<B<C] = E[B.I(A<B<C)]/P[A<B<C][/tex]

which is a ratio of integrals that should both be tractable.

Hope this helps.

Isn't this just the "law of total expectation"?

I don't really understand your point I'm afraid.

EDIT: Yes, we can also go by the second approach.

Then how to calculate [tex]E[B.I(A<B<C)][/tex] exactly ? (I'm not sure how to start with this integral.)
 
Ego7894612 said:
Isn't this just the "law of total expectation"?

I don't really understand your point I'm afraid.

EDIT: Yes, we can also go by the second approach.

Then how to calculate [tex]E[B.I(A<B<C)][/tex] exactly ? (I'm not sure how to start with this integral.)

I now understand what you mean by "I'm not sure about this line (...)": you're completely right, it's wrong!
 
Ego7894612 said:
Then how to calculate [tex]E[B.I(A<B<C)][/tex] exactly ? (I'm not sure how to start with this integral.)

Ok, this can be simplified to

[tex]\int_R b.f_A(a).f_B(b).f_C(c)da.db.dc[/tex]

where R is the region a<b<c.
 

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