Marginal probability distribution

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Discussion Overview

The discussion revolves around finding the marginal probability distributions for two random variables, X and Y, given a joint probability density function f(x,y) = 6x²y under specific constraints. Participants explore the integration process necessary to derive the marginal densities and address issues related to normalization and the correct bounds of integration.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents the joint probability density function and attempts to derive the marginal density for X, noting that it integrates correctly to 1.
  • Concerns are raised about the integration bounds used for the marginal density of Y, with suggestions that the integration should occur from 0 to y instead of 0 to 1.
  • Another participant points out that the inequalities defining the region of integration must be carefully considered, indicating that the correct bounds for X are 0 < x < 1.
  • There is a correction regarding the vertices of the triangular region defined by the inequalities, specifically that one vertex should be (1,1) instead of (1,0).
  • Some participants express frustration with the problem, indicating that it is complex and challenging to resolve.
  • One participant claims to have successfully computed the integrals and found that the total integrates to 1, providing specific values for the integrals over different ranges of y.
  • Another participant elaborates on the integration process for the marginal distribution of Y, suggesting the use of a change of variables to simplify the calculations.
  • A question is raised about the bounds for conditional probability f(y|x), with a request for clarification on whether they are the same as those for f_X(x).

Areas of Agreement / Disagreement

Participants express differing views on the correct integration bounds and the normalization of the marginal densities. There is no consensus on the correct approach to integrating for the marginal density of Y, and the discussion remains unresolved regarding the best method to establish the bounds and ensure normalization.

Contextual Notes

The discussion highlights limitations in the clarity of the integration bounds and the assumptions made about the region of integration. There are unresolved mathematical steps regarding the normalization of the marginal densities.

_joey
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I have a question I need to answer.

[tex]f\left(x,y\right)= 6x^2y[/tex] such that [tex]0<x<y[/tex] and [tex]x+y<2[/tex] where [tex]f\left(x,y\right)[/tex] is a probability density function for two random variables: [tex]X,\;Y[/tex]

I need to find marginal density distribution for the random variables [tex]X[/tex] and [tex]Y[/tex]

It appears to be a straight forward question except that when I integrate twice, in instance with the marginal density for [tex]Y,\;f_Y[/tex], it does not integrate to 1.

Here are my calculations:

[tex] 0&<&x<y[/tex] and [tex]x+y<2 \implies 0<x<1[/tex] and [tex]x<2-y[/tex]. Hence, marginal density for [tex]X[/tex] is

[tex]f_x\left(x,y\right)=\int\limits_{x}^{2-x}6x^2y\,dy =\[\left. 3{{x}^{2}}{{y}^{2}} \right|_{x}^{2-x}\]=12x^2-12x^3,\;0<x<1[/tex]

If I integrate the above function again over [tex]\left(0,1\right)[/tex]I will obtain 1. This is a property of marginal density distribution (?!)

Things start falling apart with marginal density for [tex]Y[/tex] variable

[tex]f_y\left(x,y\right)=\int\limits_{0}^{1}6x^2y\,dx =\[\left. 2{{x}^{3}}{{y}} \right|_{0}^{1}\]=2y,\;x<y<2-x[/tex]

If I integrate [tex]f_Y(y)=2y[/tex] again over [tex]x<y<2-x[/tex] I will obtain [tex]4-4x[/tex].

Any help and suggestions will be much appreciated.

Thanks!
 
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_joey said:
Things start falling apart with marginal density for [tex]Y[/tex] variable

[tex]f_y\left(x,y\right)=\int\limits_{0}^{1}6x^2y\,dx =\[\left. 2{{x}^{3}}{{y}} \right|_{0}^{1}\]=2y,\;x<y<2-x[/tex]

Shouldn't you integrate x rather from 0 to y instead of from 0 to 1?
Also note that for arbitrary value of y, x can range from 0 to 2 so your first integral for the marginal density of X is also not correct.
 
DrDu said:
Shouldn't you integrate x rather from 0 to y instead of from 0 to 1?
Also note that for arbitrary value of y, x can range from 0 to 2 so your first integral for the marginal density of X is also not correct.

We have a set of inequalities:

0<x<y and x+y<2. If you solve the inequalities, you will get 0<x<1.
0<x+x<y+(2-y)

If set inequality constraints on a plane, you will see a triangle with points (0,0) (1,0) and (0, 2). x is bounded above by 1

If we integrate from 0 to y, as you suggest, and then from x to 2-x with respect to y (y is bounded)? The volume will not be equal to 1. This is a property of marginal density
 
Ok, I was to quick. Note that the second corner of the triangle must be (1,1), not (1,0) as x must be smaller than y.
The marginal density for y is then [tex]\int_0^y dx 6x^2y[/tex] for y<1 and [tex]\int_0^{2-y} dx 6x^2y[/tex] for [tex]y \ge 1[/tex].
I'm in a hurry, hope I didn't make an error this time.
 
DrDu said:
Ok, I was to quick. Note that the second corner of the triangle must be (1,1), not (1,0) as x must be smaller than y.
The marginal density for y is then [tex]\int_0^y dx 6x^2y[/tex] for y<1 and [tex]\int_0^{2-y} dx 6x^2y[/tex] for [tex]y \ge 1[/tex].
I'm in a hurry, hope I didn't make an error this time.

Yes, point (1,1), it was a typo.

If we integrate the marginal density you obtained ([tex]12y^3-24y^2+16y[/tex]) for 2nd time to see if it is valid (and the joint distribution from which density was obtained is valid), we don't get volume equal to 1. Unless the bounds are mixed in the 2nd integration.
 
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This problem is giving me a headache.:(
 
I did the integrals and got 1. The integral over y from 0 to 1 gives 2/5 and the second one over y from 1 to 2 gives 1-2/5.
 
Could you please elaborate on how and why you are choosing these bounds or refer me to relevant information.

Thanks for your replies.
 
DrDu,

What do you think of my solution for marginal density of Y that is, for f(x,y) over (0, 1) and then over (x, 2-x)
 
  • #10
The ranges of integration are easy to find. You already identified the relevant triangle.
To get the marginal distribution of y, you have to integrate over x with y hold fixed. If y is smaller 1, x can range from 0 t0 y. If y is greater than 1, you are on the other side of the triangel and x can range from 0 to 1-y.
Hence f(y)=2y^4 for y<1 and 2(2-y)^3 y for y>1.
To confirm that the marginal density is normalized, you integrate over y. The first integral with y ranging from 0 to 1 is easy and yields 2/5, the second integral with y ranging from 1 to 2 becomes easy after introduction of z=2-y as a new variable of integration. It yields 1-2/5.
So the total integral is 1.
 
  • #11
DrDu said:
The ranges of integration are easy to find. You already identified the relevant triangle.
To get the marginal distribution of y, you have to integrate over x with y hold fixed. If y is smaller 1, x can range from 0 t0 y. If y is greater than 1, you are on the other side of the triangel and x can range from 0 to 1-y.
Hence f(y)=2y^4 for y<1 and 2(2-y)^3 y for y>1.
To confirm that the marginal density is normalized, you integrate over y. The first integral with y ranging from 0 to 1 is easy and yields 2/5, the second integral with y ranging from 1 to 2 becomes easy after introduction of z=2-y as a new variable of integration. It yields 1-2/5.
So the total integral is 1.
Thanks! I appreciate your help.
 
  • #12
Another question on bounds. It is a simple question but I lost confidence in setting up the bounds.

If I need to find conditional probability f(y|x). Then, [tex]f(y|x) = \frac{f(x,y)}{f_X(x)}[/tex]. In our case, [tex]f_X(x)}=\int\limits_{x}^{2-x}6x^2y dy = 12x^2-12x^3, 0<x<1[/tex] and [tex]f(y|x)=\frac{6x^2y}{12x^2-12x^3}=\frac{2y}{2-2x}[/tex]

Question: the bounds for [tex]f(y|x)[/tex] are the same as for [tex]f_X(x)[/tex]? That is, [tex]0<x<1[/tex] and [tex]x<y<2-x[/tex]?

Thanks
 
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