How can I find the probability of X being greater than both Y and Z?

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Discussion Overview

The discussion revolves around finding the probability that a random variable X is greater than two other random variables Y and Z. Participants explore various approaches to solve this problem, considering the dependencies between the variables and the use of statistical concepts such as order statistics.

Discussion Character

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

Main Points Raised

  • One participant presents the problem of calculating Pr[X > Y and X > Z] given certain probabilities and asks for directions to solve it.
  • Another participant suggests that the independence of Y and Z affects the calculation, proposing a formula for the case of independence.
  • Some participants clarify that Y and Z are dependent variables and inquire about the applicability of ranking schemes from Information Retrieval.
  • A participant elaborates on having multiple normal distributions with the same mean and variance, seeking to determine the probability that X is the largest among them.
  • Another participant introduces the concept of order statistics but expresses uncertainty about its application due to the non-identical distributions involved.
  • Further discussion includes the potential modification of order statistics formulas for different distributions, emphasizing the complexity of such modifications.
  • One participant raises the need for clarification on whether a symbolic, numerical, or practical answer is required for the problem.
  • A suggestion is made to compute the distribution of the maximum of the other variables and then find the probability that X exceeds this maximum.

Areas of Agreement / Disagreement

Participants generally agree on the complexity introduced by the dependence of the variables and the challenges in applying order statistics. However, there is no consensus on a definitive approach to solve the problem, and multiple competing views remain regarding the methods to be used.

Contextual Notes

Participants note limitations related to the lack of refined information about the probability density functions and the assumptions required for applying certain statistical methods.

chetkgp
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Hi,

I am stuck with the problem of solving this problem for my research.

I have 3 random variables say X, Y, and Z and say
Pr[X > Y] = p_xy, Pr[X > Z] = p_xz, and Pr[Y > Z] = 0.5.

Note that p_yx = 1 - p_xy. Similarly, p_zx = 1 - p_xz, p_yz = p_zy = 0.5

I need to find out the Pr[X > Y and X > Z] ?

Any directions to solve this problem would be of great help.
 
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It depends on whether or not Y and Z are independent. If they are:
P(X>Y and X>Z) = P(X>Y)P(X>Z) = (p_xy)(p_xz).
If they are not independent then there is no easy answer.
 
they are dependent variables.

Is there any way I can use ranking schemes that are used in Information Retrieval ?
 
chetkgp said:
they are dependent variables.

Is there any way I can use ranking schemes that are used in Information Retrieval ?

You don't have any more refined information about the probability density functions?
 
To be more specific :

I have N normal distributions, all having exactly the same mean
except for one (say X). The variance is same in all cases.

I know the probability Pr(X > Y_i), for any of the N-1 remaining distributions.
Using this I need to know the probability that X is the largest of all the distributions.

-Chester
 
chetkgp said:
To be more specific :

I have N normal distributions, all having exactly the same mean
except for one (say X). The variance is same in all cases.

I know the probability Pr(X > Y_i), for any of the N-1 remaining distributions.
Using this I need to know the probability that X is the largest of all the distributions.

-Chester

Have you come across order statistics?
 
I just read about order statistics.
I'm not sure how to apply it here because the distributions are not identical.

-Chester
 
chetkgp said:
I just read about order statistics.
I'm not sure how to apply it here because the distributions are not identical.

-Chester

You can modify those formulas for distributions that are different, as long as they are independent, so maybe you won't be able to do it.

What you should do is look at the formulation of the order statistic distribution. Look at the first statements for the derivation and see if you can either a) use those assumptions or b) create a modified version of the order statistic distribution to suit your needs.

You can create order statistics that use different distributions, but the common formula was derived with the assumption that you use the same distribution.

I have a feeling the modification won't be simple if you do find a distribution for your ordered statistic given your distributions, but it might be worth investigating particularly if your problem is important.
 
chetkgp,

You didn't say whether you need a 1) A symbolic answer or 2) A numerical answer that is easy to justify (e.g. one that comes from a symbolic expression and a well known deterministic approximation method for it) or 3) A practical numerical answer, which could come from a Monte-Carlo simulation.

You can think of the problem this way:

Let the independent random variables be [itex]X, X_1,X_2,...X_{n-1}[/itex] with [itex]X_1,X_2,..X_{n-1}[/itex] being identically distributed. Compute the distribution of [itex]Y = max \{X_1,X_2,..X_{n-1}\}[/itex] using the formulae from the theory of order statistics.

Then find the probabiity that [itex]X > Y[/itex].
 

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