MHB Proving the Uniform Distribution of Y from Independent Random Variables X

Click For Summary
If the independent identically distributed random variables X have a probability p of being 1 equal to 1/2, then the random variable Y, defined as the sum of weighted X values, is uniformly distributed over the interval [0,1]. Conversely, if p is not equal to 1/2, Y's distribution function remains continuous but is not absolutely continuous, indicating that it is singular with respect to the Lebesgue measure. The discussion highlights the mathematical derivation of these properties through the use of probability density functions and infinite products. The convergence of certain series and products plays a crucial role in establishing these results. Understanding these distributions is essential for further applications in probability theory and statistics.
bennyzadir
Messages
17
Reaction score
0
Let be $X_1, X_2, ..., X_n, ... $ independent identically distributed random variables with mutual distribution $ \mathbb{P}\{X_i=0\}=1-\mathbb{P}\{X_i=1\}=p $. Let be $ Y:= \sum_{n=1}^{\infty}2^{-n}X_n$.
a) Prove that if $p=\frac{1}{2}$ then Y is uniformly distributed on interval [0,1].
b) Show that if $p \neq \frac{1}{2}$ then the distribution function of random variable Y is continuous but not absolutely continuous and it is singular (i.e. singular with respect to the Lebesque measure, i.e with respect to the uniform distribution).

I would really appreciate if you could help me!
Thank you in advance!
 
Physics news on Phys.org
zadir said:
Let be $X_1, X_2, ..., X_n, ... $ independent identically distributed random variables with mutual distribution $ \mathbb{P}\{X_i=0\}=1-\mathbb{P}\{X_i=1\}=p $. Let be $ Y:= \sum_{n=1}^{\infty}2^{-n}X_n$.
a) Prove that if $p=\frac{1}{2}$ then Y is uniformly distributed on interval [0,1].
b) Show that if $p \neq \frac{1}{2}$ then the distribution function of random variable Y is continuous but not absolutely continuous and it is singular (i.e. singular with respect to the Lebesque measure, i.e with respect to the uniform distribution).
I would really appreciate if you could help me!
Thank you in advance!

If You set $\varphi_{n}(x)$ the p.d.f. of each $X_{n}$ and set $\Phi_{n}(\omega)=\mathcal {F} \{\varphi_{n}(x)\}$ You have that the p.d.f. of $\displaystyle Y=\sum_{n=1}^{\infty} 2^{-n}\ X_{n}$ is...

$\displaystyle \Phi(\omega)= \prod_{n=1}^{\infty} \Phi_{n}(\omega)$ (1)

If $p=\frac{1}{2}$ is...

$\displaystyle \varphi_{n} (x)= \frac{1}{2}\ \delta(x) + \frac{1}{2}\ \delta(x-\frac{1}{2^{n}}) \implies \Phi_{n}(\omega)= e^{- i \frac{\omega}{2^{n+1}}}\ \cos \frac {\omega}{2^{n}}$ (2)

Now You have to remember that is...

$\displaystyle \frac{\sin \omega}{\omega}= \prod_{n=1}^{\infty} \cos \frac{\omega}{2^{n}}$ (3)

... to obtain from (1) and (2)...

$\displaystyle \Phi(\omega)= e^{-i\ \frac{\omega}{2}}\ \frac{\sin \omega}{\omega}$ (4)

... so that Y is uniformly distributed between 0 and 1...

Kind regards

$\chi$ $\sigma$
 
Last edited:
Thank you for your answer. Do you have any idea for part b) ?
 
If $p \ne \frac{1}{2}$ the task becomes a little more complex. In that case You have...

$\displaystyle \varphi_{n}(x)= p\ \delta(x) + (1-p)\ \delta (x-\frac{1}{2^{n}}) \implies \Phi_{n} (\omega)= (1-p)\ e^{- i \frac{\omega}{2^{n}}}\ (1+ \frac{p}{1-p}\ e^{i \frac{\omega}{2^{n}}})$ (1)

... and now You have to valuate the 'infinite product'...

$\displaystyle \Phi(\omega)= \prod_{n=1}^{\infty} \Phi_{n}(\omega)$ (2)

What You can demonstrate is that the infinite product (2) converges because converges the term...

$\displaystyle \prod_{n=1}^{\infty} (1+ \frac{p}{1-p}\ e^{i \frac{\omega}{2^{n}}})$ (3)

... and that is true because converges the series...

$\displaystyle \sum_{n=1}^{\infty} e^{i \frac{\omega}{2^{n}}}$ (4)

The effective computation of (2) is a different task that requires a little of efforts...

Kind regards

$\chi$ $\sigma$
 
There is a nice little variation of the problem. The host says, after you have chosen the door, that you can change your guess, but to sweeten the deal, he says you can choose the two other doors, if you wish. This proposition is a no brainer, however before you are quick enough to accept it, the host opens one of the two doors and it is empty. In this version you really want to change your pick, but at the same time ask yourself is the host impartial and does that change anything. The host...

Similar threads

  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 6 ·
Replies
6
Views
4K
Replies
2
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K