Conditional Distribution Functions

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SUMMARY

The discussion centers on finding the joint and marginal distributions of two random variables, X1 and X2, where X1 is uniformly distributed on [0,1] and X2 is uniformly distributed on [0,X1] given X1. The joint density function is established as f(X1,X2) = 1/X1, applicable within a specified region in the (X1,X2) space. The marginal distribution of X2 requires integration of the joint density, but the original poster encounters issues with notation and integration limits, leading to confusion over the density function's behavior.

PREREQUISITES
  • Understanding of conditional distributions in probability theory
  • Familiarity with joint and marginal distributions
  • Knowledge of uniform distributions and their properties
  • Basic integration techniques in calculus
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  • Study the derivation of joint distributions from conditional distributions
  • Learn about the properties and applications of uniform distributions
  • Explore integration techniques for finding marginal distributions
  • Investigate common notations used in probability and statistics to avoid confusion
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Students and professionals in statistics, data science, and probability theory who are working on joint and marginal distributions, particularly in the context of conditional relationships between random variables.

Brandon1994
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Homework Statement


If X1 is uniform on [0,1], and, conditional on X1, X2, is uniform on [0,X1], find the joint and marginal distributions of X1 and X2


Homework Equations



conditional joint distribution

The Attempt at a Solution



f(x1|x2) = 1/x1 (for 0<x2<x1)
f(x1) = 1 ( for 0<x1<1)

then
F(x1,x2) = Integrate (1/x1) from {x2,0,x2}{x1,0,x1}
I get an ln(0) when i try to integrate however

for the marginal distribution of x2, i get X2~[0,X1] //i am not sure if that's the answer they are looking for, if i try to write an explicit density function for X2 i get that the density is infinity, again due to the ln (0) term.

Thanks
 
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Brandon1994 said:

Homework Statement


If X1 is uniform on [0,1], and, conditional on X1, X2, is uniform on [0,X1], find the joint and marginal distributions of X1 and X2


Homework Equations



conditional joint distribution

The Attempt at a Solution



f(x1|x2) = 1/x1 (for 0<x2<x1)
f(x1) = 1 ( for 0<x1<1)

then
F(x1,x2) = Integrate (1/x1) from {x2,0,x2}{x1,0,x1}
I get an ln(0) when i try to integrate however

for the marginal distribution of x2, i get X2~[0,X1] //i am not sure if that's the answer they are looking for, if i try to write an explicit density function for X2 i get that the density is infinity, again due to the ln (0) term.

Thanks

You have it exactly backwards: you are given ##f(x_2|x_1)##, not ##f(x_1|x_2).##

Also: what does the notation "Integrate(1/x1) from {x2,0,x2}{x1,0,x1}" mean? I have never seen that before.

Anyway, the first thing to do is to answer the question "what is the joint distribution of ##(X_1,X_2)?## You have not done that.
 
wouldn't the joint density be:
f(X1,X2) = 1/X1

and I was saying to find the marginal density f(X2) you would integrate the above expression
 
Brandon1994 said:
wouldn't the joint density be:
f(X1,X2) = 1/X1

and I was saying to find the marginal density f(X2) you would integrate the above expression

Yes, f(x1,x2) = 1/x1, bit only on an appropriate region in (x1,x2)-space. You need to spell out the details.

Of course you need to do an integral to get the marginal distibution of x2, but that was not the point. I asked what you meant by the weird notation "Integrate(1/x1) from {x2,0,x2}{x1,0,x1}". This looks like something you invented that nobody else knows about, but surely you must have in mind some meaning for it. I am asking you to explain that meaning---in detail, not just saying that you need to integrate. That is: what is the integration variable, and what are the limits of integration?Even better, what is the final answer you get?
 

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