Let X be uniformly distributed on (0,1)

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Discussion Overview

The discussion revolves around demonstrating that the random variable Y, defined as Y = -λ⁻¹ ln(1-X) where X is uniformly distributed on (0,1), follows an exponential distribution with parameter λ > 0. The scope includes mathematical reasoning and technical explanations related to probability distributions and moment generating functions.

Discussion Character

  • Mathematical reasoning
  • Technical explanation

Main Points Raised

  • One participant poses the initial question about showing that Y has an exponential distribution.
  • Another participant suggests using moment generating functions (MGFs) to prove the distribution type, indicating that if two distributions have the same MGF, they are of the same type.
  • A participant provides a detailed approach using the MGF of Y, including the integral setup and substitution to derive the MGF corresponding to the exponential distribution.
  • Another participant mentions using the standard formula for computing the density of a strictly increasing function, relating the density of Y to that of X through a transformation.

Areas of Agreement / Disagreement

Participants present various methods to approach the problem, but there is no consensus on a single method or resolution of the question posed. Multiple perspectives on how to demonstrate the distribution type remain evident.

Contextual Notes

Some participants reference generating functions and moment generating functions without fully resolving the implications of their approaches. The discussion includes assumptions about the properties of the uniform distribution and transformations applied to it.

TomJerry
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Question:
Let X be uniformly distributed on (0,1). Show that Y=- [tex]\lambda[/tex]-1 1n(1-X) has an exponential distribution with parameter [tex]\lambda[/tex]>0
 
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Do you know what generating functions are?
 
let

[tex] F_Y(y) = P(Y \le y)[/tex]

and use the definition of [itex]Y[/itex] to rewrite the inequality in terms of [itex]X[/itex].
 
chiro said:
Do you know what generating functions are?

Nope !
 
Here is how you can do this with a moment generating function.

Basically you can prove that a distribution is a particular one if both moment generating functions are of the same type.

So for example you've given Y = - 1/(lambda) ln(1 - X).

We are given that X is uniform on (0,1) so basically standard uniform.

The PDF of X is simply 1 with the domain (0,1).

The MGF of Y is given by M(t) = E[e^(Yt)] = Integral [0,1] 1 x e^(-{1/lambda} x ln{1-x} x t) dx = Integral [0,1] (1-x)^(-t/{lambda})

Using a substitution we get u = 1 - x, du = -dx which gives us the integral

M(t) = Integral [0,1] u^(-t/{lambda}) du.

This gives us M(t) = 1/{-t/lambda + 1} which corresponds to the MGF of the exponential distribution.
 
You can also use the standard formula for computing the density of a strictly increasing function. If X has density f_X(x) and Y=g(X) is strictly increasing, then Y has density f_Y(y)=f_X(g^-1(y))*dg^-1(y)/dy
 

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