Transformation of f(x,y) = 1 to f(z) where Z=XY

In summary, the correct answer is -ln(z), 0<z<1, though it's amiguous as to whether that's the cdf or pdf.
  • #1
rayge
25
0
This is from a chapter on distributions of two random variables. Let X and Y have the pdf f(x,y) = 1, 0<x<1 and 0<y<1, zero elsewhere. Find the cdf and pdf of the product Z=XY.

My current approach has been to plug in X=Z/Y in the cdf P(X<=x) , thus P(Z/Y<=x), and integrate over all values of Y. The integral I've tried to solve is ∫(0 to 1)∫(0 to Z/Y) 1 dxdy (sorry for the formatting).

This is somehow wrong, because from that integral I get z*(ln(1) - ln(0)), which is undefined (unless I'm solving the integral incorrectly, which would actually be a relief).

The correct answer is -ln(z), 0<z<1, though it's amiguous as to whether that's the cdf or pdf.

Thanks for any solutions or suggestions about where my approach is going wrong.
 
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  • #2
-ln(z) is a density function.

When doing the integral note that the upper limit on x is min(1,z/y).
 
  • #3
Another way of seeing the same thing... [It looks a little less direct, but there's value in thinking about sums of exponential random variables.]

Let [itex]\tilde X = -ln(X)[/itex], [itex]\tilde Y = -ln(Y)[/itex], and [itex]\tilde Z = -ln(Z) = \tilde X+\tilde Y[/itex], all taking values on [itex](0,\infty)[/itex]. Define the CDF [itex]G(\tilde x)= P(\tilde X\leq \tilde x)= P(X\geq e^{-\tilde x})=1-e^{-\tilde x}[/itex], which is of course also the CDF of [itex]\tilde Y[/itex]. Differentiating, we get the PDF [itex]g(\tilde x)=e^{-\tilde x}[/itex]. Now we can compute [tex]P(\tilde Z> \tilde z\geq \tilde X) = \int_0^{\tilde z} P(\tilde x+\tilde Y> \tilde z) g(\tilde x) \text{d}\tilde x = \int_0^{\tilde z} [1- G( \tilde z-\tilde x)] g(\tilde x) \text{d}\tilde x = \int_0^{\tilde z} e^{\tilde x-\tilde z} e^{-\tilde x} \text{d}\tilde x = \int_0^{\tilde z} e^{-\tilde z} \text{d}\tilde x = \tilde z e^{-\tilde z}.[/tex] This yields [tex]P(Z<z\leq X) = P(\tilde Z> -ln(z)\geq \tilde X) = [-ln(z)]z.[/tex] Finally, we notice that (as [itex]Z\leq X[/itex]) [tex]P(Z<z)=P(X<z)+P(Z<z\leq X) = z - [-ln(z)]z = [1-ln(z)]z.[/tex] If your end goal is a density, you can differentiate for a PDF of [itex]-ln(z)[/itex].
 
  • #4
Thanks for the responses. Before I dive into economicsnerd's solution (wow), I'm a bit confused by min(1,Z/Y). When Z<Y, min(1,Z/Y) is Z/Y. When Z>Y, it's 1. So...

∫(0 to 1)∫(0 to Z/Y)dxdy where 0<z<y<1
∫(0 to z)∫(0 to 1)dxdy where 0<y<z<1

Isn't the first integral still undefined? Or am I applying this incorrectly?
 
  • #5
The CDF of [itex]Z[/itex] is [tex]F(z)= P(Z\leq z) = 1- P(Z>z) = 1-P(X\geq Z > z) = 1-\int_z^1 \int_{\frac{z}{x}}^1 1\enspace \text{d}y \enspace \text{d}x = 1-\int_z^1 \left(1-\frac{z}{x}\right) \enspace \text{d}x.[/tex] What do you get when you compute that integral?
 
  • #6
I get your solution. Awesome.

I'm confused as to why P(Z>z) = P(X>=Z>z). Are we able to say this since 0<x<1, 0<y<1, so any multiplication of x and y is less than x and y? I just never would've seen that.

I'm also stumped about the construction of this integral. The outer integral z to 1 dx is fine, but why do we choose z/x as the lower limit of the integral over dy? When we plug in z/x for y in the equation 0<y<1, we get 0<z/x<1... and from this it's still not clear to me that z/x is the lower limit.

edit: it's probably because we flipped P(Z<z) to P(Z>z)...

Thanks for your help!
 

1. What is the purpose of transforming f(x,y) = 1 to f(z) where Z=XY?

The purpose of transforming f(x,y) = 1 to f(z) where Z=XY is to simplify the function and make it easier to work with. This transformation allows us to represent the function in terms of a single variable, z, instead of two variables, x and y.

2. How is the transformation of f(x,y) = 1 to f(z) where Z=XY carried out?

The transformation of f(x,y) = 1 to f(z) where Z=XY is carried out by substituting z for xy in the original function. This transformation is also known as a change of variables.

3. What are the benefits of transforming f(x,y) = 1 to f(z) where Z=XY?

Transforming f(x,y) = 1 to f(z) where Z=XY allows us to simplify calculations and make them more efficient. It also helps us to better understand the behavior of the function and its relationships with other variables.

4. Can f(z) where Z=XY be transformed back to f(x,y) = 1?

Yes, f(z) where Z=XY can be transformed back to f(x,y) = 1 by reversing the substitution process. This means substituting xy back in for z in the transformed function.

5. Are there any limitations to transforming f(x,y) = 1 to f(z) where Z=XY?

One limitation of transforming f(x,y) = 1 to f(z) where Z=XY is that it may not always be possible to do so. This transformation is only valid when the original function can be expressed in terms of a single variable. Additionally, the transformed function may not accurately represent the original function in all cases.

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