Maximum of two correlated random variables

In summary, the individual is seeking an analytical or approximate solution for finding the maximum of two correlated, non-gaussian random variables A and B. They mention a method by Clark that assumes gaussian correlated variables, but are looking for a solution that does not make this assumption. They also mention a potential method using quadratic taylor polynomials and finding the maximum through the formula (A+B+abs(A-B))/2, but are unsure if they can approximate abs(A-B) without regression. They are seeking any direction or solution for this problem.
  • #1
touqeerazam
6
0
Hi all,

I want to find maximum of two random variables which are correlated and are non gaussian too. Baiscally I need an analytical orr approximate solution to their bivaraite distribution with means and varaince of resulting distribution. There is some work by Clark 'The greatest of finite set of random variables' but that assumes gaussian correlated variables.

so if A & B are two correlated random varaibles. I need C=Max(A,B)?

one other method is to use quadratic taylor polynomial for A & B. and use Max (A,B)=(A+B+abs(A-B))/2. But I don't know can i approximate abs(A-B) by quadratic polynomial (without regression). In other words, if I can get any method to approximate abs(A-B) by analytical expression. This will also give me Max operation (what I really need).

Sorry for long question

I will be very grateful to you if anyone could figure out solution or any directions

cheers
Touqeer
 
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  • #2
Are you given the joint distribution f of Aand B? then you could try and compute the distribution of C=max(A,B) as

[tex]
\mathbb{P}(C\leq c)=\int_{-\infty}^c{da\,\int_{-\infty}^a{db\,f(a,b)}}+\int_{-\infty}^c{db\,\int_{-\infty}^b{da\,f(a,b)}}.
[/tex]
 
  • #3
Hi,

Thanks Pere. I don't have their joint dis 'f'. Its difficult to get JPDF of correlated non gaussian variables (not sure how to get). What all I have is varaible A & B given as,

A=a0+a1x+a2x^2+a3y+a4y^2
B=b0+b1x+b2x^2+b3y+b4y^2

where x & y are two parameters which are correlated non gaussian, and I have their PDFs. ai's and bi's are just coefficients.

Can you please point out any solution?

Thanks
Touqeer
 

FAQ: Maximum of two correlated random variables

What is the maximum of two correlated random variables?

The maximum of two correlated random variables is the value that is higher than or equal to both variables. It represents the highest possible outcome when considering both variables together.

How is the maximum of two correlated random variables calculated?

The maximum of two correlated random variables is calculated by finding the largest value of each variable, and then comparing them to determine which is the highest. If the variables are positively correlated, the maximum will be the sum of the two values minus their covariance. If the variables are negatively correlated, the maximum will be the difference between the two values plus their covariance.

What is the significance of the maximum of two correlated random variables?

The maximum of two correlated random variables is important in understanding the relationship between the two variables. It can provide insights into the strength and direction of the correlation, as well as the potential range of values that can be expected when considering both variables together.

Can the maximum of two correlated random variables be used to predict future outcomes?

While the maximum of two correlated random variables can provide some information about the relationship between the two variables, it is not a reliable predictor of future outcomes. This is because correlation does not imply causation, and there may be other factors at play that influence the variables and their outcomes.

How does the maximum of two correlated random variables differ from the maximum of independent random variables?

The maximum of two correlated random variables differs from the maximum of independent random variables in that the former takes into account the correlation between the two variables, while the latter does not. In the case of independent variables, the maximum will simply be the larger of the two values, without any adjustments for their correlation.

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