The distribution of ratio of two uniform variables

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Discussion Overview

The discussion revolves around the calculation of the density of the ratio of two independent uniform random variables, specifically U=Y/X where X and Y are uniformly distributed over (0,1). Participants explore the integration steps involved in deriving the marginal distribution of U and address related questions about cumulative distribution functions (CDFs) of other random variables.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant, referred to as gim, attempts to derive the density function of U and expresses confusion about the integration resulting in a value of 1/2, questioning where the error lies.
  • Another participant suggests that gim only integrated with respect to U and should also integrate with respect to V, proposing the use of a double integral to clarify the calculation.
  • Gim reiterates the focus on the marginal distribution of U and emphasizes that the result of 1/2 is problematic as it does not integrate to 1, indicating a misunderstanding or miscalculation in the density function.
  • Several posts introduce a separate question regarding the CDF of the random variable Z=min(X,Y), with participants seeking clarification on the computation of this CDF based on the joint CDF of X and Y.
  • One participant expresses difficulty in starting a new thread and attempts to relate the problem to the PDF of an exponential function, indicating a struggle to connect the concepts involved.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the correct approach to deriving the density function of U, and there are multiple competing views regarding the integration methods and the implications of the results. The discussion about the CDF of Z also introduces additional questions without resolution.

Contextual Notes

There are limitations in the integration steps discussed, particularly regarding the assumptions made about the independence of the random variables and the handling of the joint distribution. Some mathematical steps remain unresolved, contributing to the uncertainty in the results presented.

gimmytang
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Hello,
Let X ~ U(0,1), Y ~U(0,1), and independent from each other. To calculate the density of U=Y/X, let V=X, then:
[tex]f_{U,V}(u,v)=f_{X,Y}(v,uv)|v|[/tex] by change of variables.
Then:
[tex]f_{U}(u)=\int_{0}^{1}{f_{X,Y}(v,uv)|v|dv}=\int_{0}^{1}{vdv}={1\over 2}, 0<u<\infty[/tex], which is not integrated to 1.
Where I am wrong?
gim :cry:
 
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you only integrated with respect to fu(u). Now you have to integrate with respect to fv(v). Or you could have just used a double integral to start with...
 
Actually the marginal distribution of U, namely the distribution of the ratio of two uniform variables, is the only thing that I am interested. To be more clear:
[tex]f_{U}(u)={\int_{-\infty}^{\infty}f_{U,V}(u,v)dv}={\int_{0}^{1}f_{X,Y}(u,uv)|v|dv}={\int_{0}^{1}vdv}=1/2[/tex]
Now the question is my result 1/2 is not a reasonable density since it's not integrated to 1.
gim :bugeye:
 
Question says Let X and Y be independent random variables with join cumulative distribution function (CDF) F subscript X,Y of (x,y)= P (X</= x, Y</=y). Show that the CDF Fz(z) of the random variable Z=min (X,Y) can be computed via
Fz(z)= Fx(z) + Fy(z) - Fx(z) . Fy(z) = 1 - (1 - Fx (z)) . (1- Fy (z))

Please reply to this asap. I need to submit this answer by Friday. Thanks!
 
electroissues said:
Question says Let X and Y be independent random variables with join cumulative distribution function (CDF) F subscript X,Y of (x,y)= P (X</= x, Y</=y). Show that the CDF Fz(z) of the random variable Z=min (X,Y) can be computed via
Fz(z)= Fx(z) + Fy(z) - Fx(z) . Fy(z) = 1 - (1 - Fx (z)) . (1- Fy (z))

Please reply to this asap. I need to submit this answer by Friday. Thanks!
Don't jump into the thread of another. What have you done so far?
 
Well, I'm new here and had problems starting a new thread.

I looked at PDF of an exponential function which is (1 - Fx (x)) and also since its also given its independent, we know it can be split into Fx (x) . Fy (y) but I can't put these things together.
 

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