A broken stick problem: find distribution

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SUMMARY

The discussion focuses on integrating out the variable x in the context of finding the marginal distribution of a random variable Y. The participant successfully derives the marginal distribution function, f_Y(y), which is defined as f_Y(y) = -log(y) for 0 < y < x < 1, and is zero when x < y < 1. The integration confirms that the marginal distribution integrates to 1, validating the approach taken. The use of the indicator function, \(\mathbf{1}_{(0,x)}(y)\), plays a crucial role in determining the non-zero values of the distribution.

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psie
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Homework Statement
A stick lies on the interval ##[0,1]##, and is broken at the point ##X\in U(0,1)##. The left part is then broken again at the point ##Y\in U(0,X)##, i.e the conditional pdf of ##Y## given ##X## is ##f_{Y|X=x}(y)= \mathbf{1}_{(0,x)}(y)\frac1x##, ##0<y<x##, ##0<x<1##. Find the unconditional distribution of ##Y##.
Relevant Equations
We have ##f_{Y|X=x}(y)=\frac{f_{X,Y}(x,y)}{f_X(x)}##. Since ##X## is uniformly distributed on ##(0,1)##, ##f_X(x)=1## and thus ##f_{Y|X=x}(y)=f_{X,Y}(x,y)##.
So I'd like to "integrate out" the ##x##-variable, like $$f_Y(y)=\int_0^1 \mathbf{1}_{(0,x)}(y)\frac1x\,dx.$$ I am a bit hesitant on how to proceed, since I feel like I will get an unbounded density. Something's fishy, but I don't know what.
 
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##\mathbf 1_{(0,x)}(y)## is a function of both x and y. For what values of y is it non-zero?

Edit: I get something very well defined for the marginal distribution that very nicely integrates to 1.
 
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Ok, I get that ##f_Y(y)## is ##0## when ##x<y<1## because then ##\mathbf{1}_{(0,x)}(y)=0##. For ##0<y<x##, we have that ##\mathbf{1}_{(0,x)}(y)=1## and ##y<x<1##, so $$f_Y(y)=\int_y^1 \frac1x\,dx=-\log(y).$$And integrating this over ##0<y<1## does indeed give ##1##. Thanks! :smile:
 

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