Find the joint distribution of 2 R.V defined on a triangular support

In summary: I have solved the problem. Thanks everyone.In summary, the joint distribution function F(X,Y) for the given joint density function is given by c*((x^3)/2 + (x^4)/3) whenever y<=x, and 1 for all other values of x and y. The proper integration limits for u and v are (0,x) and (0,x) for the first case, and (0,y) and (0,y) for the second case.
  • #1
infk
21
0
Find the joint CDF of 2 R.V with joint PDF of triangular support

Homework Statement


Given the 2 random variables X and Y, their joint density given by:
f(x,y) = c(x + y^2) for all (x,y) in the triangle 0<y<x<1
and f(x,y) = 0 elsewhere.
Compute the joint distribution function F(X,Y)

Homework Equations


The joint distribution is given by:
F(X,Y) = P(X[itex]\leq[/itex]x, Y [itex]\leq[/itex]y )


The Attempt at a Solution


Integrate f(u,v) over the region A:= (u,v): u[itex]\in[/itex](-∞,x), v [itex]\in[/itex] (-∞,y):
Due to the trianglular support, the region A becomes u[itex]\in[/itex](0,x), v [itex]\in[/itex] (0,y)

c[itex]\int[/itex][itex]\int[/itex]u+v^2dudv = c[itex]\int[/itex]([itex]\int[/itex]u+v^2du)dv = c[itex]\int[/itex][x^2 +xv^2] = c*((yx^2)/2 + (y^3)/3).
But this does not seem to be correct at all, the distribution should tend to 1 as (x,y) [itex]\rightarrow[/itex] ∞ and tend to 0 as (x,y) [itex]\rightarrow[/itex] -∞

Edit:
I realized that the formula F(X,Y) = P(X[itex]\leq[/itex]x, Y [itex]\leq[/itex]y ) is incomplete, since that the expression Y [itex]\leq[/itex]y requires that y be less than x So maybe the correct answer is F(x,y) = c*((yx^2)/2 + (y^3)/3), whenever y[itex]\leq[/itex] x. I also integrated the density function f(u,v) over u[itex]\in[/itex](0,x), v [itex]\in[/itex] (0,x) and arrived at the expression c((x^3)/2 + (x^4)/3).. Does this seem resonable?
 
Last edited:
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  • #2


infk said:

Homework Statement


Given the 2 random variables X and Y, their joint density given by:
f(x,y) = c(x + y^2) for all (x,y) in the triangle 0<y<x<1
and f(x,y) = 0 elsewhere.
Compute the joint distribution function F(X,Y)

Homework Equations


The joint distribution is given by:
F(X,Y) = P(X[itex]\leq[/itex]x, Y [itex]\leq[/itex]y )

The Attempt at a Solution


Integrate f(u,v) over the region A:= (u,v): u[itex]\in[/itex](-∞,x), v [itex]\in[/itex] (-∞,y):
Due to the trianglular support, the region A becomes u[itex]\in[/itex](0,x), v [itex]\in[/itex] (0,y)

c[itex]\int[/itex][itex]\int[/itex]u+v^2dudv = c[itex]\int[/itex]([itex]\int[/itex]u+v^2du)dv = c[itex]\int[/itex][x^2 +xv^2] = c*((yx^2)/2 + (y^3)/3).
But this does not seem to be correct at all, the distribution should tend to 1 as (x,y) [itex]\rightarrow[/itex] ∞ and tend to 0 as (x,y) [itex]\rightarrow[/itex] -∞

Edit:
I realized that the formula F(X,Y) = P(X[itex]\leq[/itex]x, Y [itex]\leq[/itex]y ) is incomplete, since that the expression Y [itex]\leq[/itex]y requires that y be less than x So maybe the correct answer is F(x,y) = c*((yx^2)/2 + (y^3)/3), whenever y[itex]\leq[/itex] x. I also integrated the density function f(u,v) over u[itex]\in[/itex](0,x), v [itex]\in[/itex] (0,x) and arrived at the expression c((x^3)/2 + (x^4)/3).. Does this seem resonable?

Integrate f(x,y) over the intersection of the rectangle [0,x]×[0,y] and the triangle 0 < y < x < 1. Draw a picture first! This will show clearly that your statement "...requires that y be less than x" in F(x,y) is false: I can certainly compute F(1/2, 3/4) and it makes sense to ask what is the probability of the event {X ≤ 1/2, Y ≤ 3/4}.

RGV
 
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  • #3
Thanks for the reply.
I do realize that it makes sense to ask for F(x,y) for any values of x and y.
Ofcourse, one must integrate over the intersection of the rectangle (0,x) x (0,y) and the triangle where f(x,y) is non-zero.

I have tried setting the limits for y to be (0, min(x,y)) but that's it.

I have been stuck on this for days, any further advice would be deeply appreciated.
 
  • #4
Let me repeat: draw a picture.

RGV
 
  • #5
Ray Vickson said:
Let me repeat: draw a picture.

RGV

Believe me, I have drawn many.

I believe the problem boils down to finding the proper integration limits of u and v in the integral:
[itex]\int\int[/itex]f(u,v)dudv.
Obviously, u and v should both positive. What I have come up with so far is this:
P(X [itex]\leq[/itex] x, Y [itex]\leq[/itex] y) must be 1 whenever x and y are greater than or equal to one. (Equivalently, when the triangular support of f(x,y) is contained within the rectangle (0,x] x (0,y]).Whenever the triangle is not contained within the rectangle (0,x] x (0,y], we can split this in two cases:

1. the rectangle (0,x] x (0,y] is such that y [itex]\geq[itex] x.
In this case, the intersection of the rectangle and the triangle is simply the isosceles triangle with corner points (0,0), (x,x) and (x,0).
we should thus integrate u over (0,x) and v over (0,x). The result will then depend solely on x. (Is that plausible?) 2. the rectangle (0,x] x (0,y] is such that x < y.
In this case, the intersection is partly the isosceles triangle with corner points (0,0), (y,y) and (y,0). the other part of the intersection is the rectangle with corner points (y,0), (x,0) ,(y,y) and (x,y).
 
  • #6
infk said:
Believe me, I have drawn many.

I believe the problem boils down to finding the proper integration limits of u and v in the integral:
[itex]\int\int[/itex]f(u,v)dudv.
Obviously, u and v should both positive. What I have come up with so far is this:
P(X [itex]\leq[/itex] x, Y [itex]\leq[/itex] y) must be 1 whenever x and y are greater than or equal to one. (Equivalently, when the triangular support of f(x,y) is contained within the rectangle (0,x] x (0,y]).Whenever the triangle is not contained within the rectangle (0,x] x (0,y], we can split this in two cases:

1. the rectangle (0,x] x (0,y] is such that y [itex]\geq[itex] x.
In this case, the intersection of the rectangle and the triangle is simply the isosceles triangle with corner points (0,0), (x,x) and (x,0).
we should thus integrate u over (0,x) and v over (0,x). The result will then depend solely on x. (Is that plausible?) 2. the rectangle (0,x] x (0,y] is such that x < y.
In this case, the intersection is partly the isosceles triangle with corner points (0,0), (y,y) and (y,0). the other part of the intersection is the rectangle with corner points (y,0), (x,0) ,(y,y) and (x,y).

1. When y > x, P{X <= x, Y <= y} = P{X <= x, Y <= x} because P{Y>X}=0. So, yes, what you said is reasonable.
2. You have it. Now just do the integrations.

RGV
 
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Related to Find the joint distribution of 2 R.V defined on a triangular support

1. What is a joint distribution?

A joint distribution is a probability distribution that describes the probability of two or more random variables occurring simultaneously. It shows the relationship between the variables and how they can affect each other.

2. What is a triangular support?

A triangular support is a type of probability distribution where the probability is concentrated within a triangular-shaped area. It is often used to represent variables that have a limited range of possible values.

3. How do you find the joint distribution of two random variables defined on a triangular support?

To find the joint distribution of two random variables defined on a triangular support, you would need to first determine the marginal distributions of each variable. Then, you can use the multiplication rule to find the joint distribution by multiplying the probabilities of each variable occurring together at a specific point.

4. Why is it important to find the joint distribution of two random variables?

Finding the joint distribution of two random variables allows us to understand the relationship between the variables and how they can affect each other. It also helps us to make predictions and analyze the behavior of the variables in different scenarios.

5. What are some real-life examples of using the joint distribution of two random variables defined on a triangular support?

One example could be predicting the likelihood of a student passing a math test based on their hours of studying and their level of confidence. Another example could be analyzing the relationship between a person's income and their level of education in a certain population.

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