Calculation of E[X|X>Y] for Exponential Random Variables

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In summary, you need a double integral to calculate the unconditional expectation of a random variable.
  • #1
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Hi, Initially X and Y are exponential random variables with rate respectively $$\mu \lambda$$, and I am aware that E[X|X>Y] is obtained using joint distribution but I can not build up the integral structure, I intuitively think the result is just 1/mu, but I can not prove it to myself could you help me about that and building the integral structure?
 
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  • #2
Start by writing the double integral that calculates the unconditional expectation ##E[X]##. Use ##x## as integration variable for the outer integral, and ##y## for the inner integral. Once you've done that, only a minor adjustment is needed to the inner integration limits to turn it into the conditional expectation ##E]X|X>Y]##.
 
  • #3
hi, I tried to do my work related to E(X1|X1<X2)*P(X1<X2), and X1, X2 are exponential random variables with rate respectively $$\lambda, \mu$$ I found a answer but I think it is wrong so could you tell me which part of my work is wrong?? ( I also looking forward to your answers @andrewkirk @Ray Vickson :) )
 

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  • #4
Did you read my post? I told you that you need a double integral. Why have you tried to do something using only a single integral? The image you posted is too dark and smudgy to make out in detail what it says but even at a glance one can see that it only has single integrals, not double integrals.
 
  • #5
@andrewkirk @Ray Vickson I upload my work 2 ,let me express again that E(X1|X1<X2)*P(X1<X2), and X1, X2 are exponential random variables with rate respectively $$\lambda_1,\lambda_2$$I found a answer but I think it is wrong so could you tell me which part of my work is wrong?? ( by the way I did my best to make it not dark, when I upload, the top and bottom parts get dark a little )
 

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  • #6
mertcan said:
Hi, Initially X and Y are exponential random variables with rate respectively $$\mu \lambda$$, and I am aware that E[X|X>Y] is obtained using joint distribution but I can not build up the integral structure, I intuitively think the result is just 1/mu, but I can not prove it to myself could you help me about that and building the integral structure?

Are X and Y independent? In any case, you first need to find $$\mathbb{E}[X|Y, X>Y]$$. To do this, first write $$\mathbb{E}[X]$$, and then change the lower limit. After finding $$\mathbb{E}[X|Y, X>Y]$$, you will need to average over all values of Y. If you go through these steps, you should be able to find what you want.
 

Related to Calculation of E[X|X>Y] for Exponential Random Variables

What is the meaning of "Expectation of E[X|X>Y]"?

The expectation of E[X|X>Y] refers to the expected value of a random variable X, given that X is greater than another random variable Y. In other words, it is the average value of X when it is known that X is larger than Y.

How is the expectation of E[X|X>Y] calculated?

The calculation of the expectation of E[X|X>Y] involves taking the sum of the products of each possible value of X and its corresponding probability, given that it is greater than Y. This can also be expressed as the integral of X multiplied by its conditional probability density function.

Why is the expectation of E[X|X>Y] important in statistics?

The expectation of E[X|X>Y] is an important concept in statistics because it allows us to understand the average value of a random variable X in a specific situation, where X is known to be larger than another random variable Y. This can provide valuable insights in various fields such as finance, economics, and engineering.

How does the expectation of E[X|X>Y] differ from the overall expectation of X?

The overall expectation of X takes into account all possible values of X, while the expectation of E[X|X>Y] only considers values of X that are greater than Y. This means that the overall expectation of X may be different from the expectation of E[X|X>Y] in situations where X is not always greater than Y.

Can the expectation of E[X|X>Y] be negative?

Yes, the expectation of E[X|X>Y] can be negative. This can occur if the values of X that are greater than Y are mostly negative, or if the probability of X being greater than Y is very small. In such cases, the average value of X given that it is greater than Y may be negative.

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