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24 votes
3 answers
30k views

Proof of the Box-Muller method

This is Exercise 2.2.2 from Achim Klenke: »Probability Theory — A Comprehensive Course«. Exercise (Box–Muller method): Let $U$ and $V$ be independent random variables that are uniformly distributed ...
Ystar's user avatar
  • 2,916
2 votes
1 answer
2k views

$X$,$Y$,$Z$ mutually independent implies $X+Y$ independent of $Z$

Supposing $X$, $Y$ and $Z$ and mutually independent real random variables, how can we prove that $X+Y$ and $Z$ are independent from the definition? If not from the definition, using $\sigma$-algebras? ...
Kika's user avatar
  • 105
2 votes
1 answer
1k views

Using the first and second Borel-Cantelli Lemma to find necessary and sufficient condition for convergence in probability ($98\%$ solved)

I am working an exercise with five parts, and I've solved most of them, but still have some little but nontrivial confusions. The parts (b)-(e) coincides with Durrett 1.6.15 or Durrett 2.3.15, and ...
JacobsonRadical's user avatar
3 votes
1 answer
909 views

Proof verification : $X_n \to X$ in distribution, $Y_n \to 0$ in probability $\implies$ $X_nY_n \to 0$ in probability

I have to show : $X_n \to X$ in distribution, $Y_n \to 0$ in probability $\implies$ $X_nY_n \to 0$ in probability. Let $\alpha>0, \epsilon>0$. Then $\exists \delta>0$ such that $-\epsilon/\...
Adi's user avatar
  • 142
2 votes
1 answer
468 views

Law of Large Numbers for a Brownian Motion

I am self-learning introductory stochastic calculus from A first course in Stochastic Calculus by L.P.Arguin. The part(c) of the below exercise problem on the time-inversion property of Brownian ...
Quasar's user avatar
  • 5,450
9 votes
1 answer
5k views

Proof of $Y=F_X(X)$ being uniformly distributed on $[0,1]$ for arbitrary continuous $F_X$

This question is related to Showing that Y has a uniform distribution if Y=F(X) where F is the cdf of continuous X, with the difference being that $F_X$ (the probability distribution function of ...
syeh_106's user avatar
  • 3,145
6 votes
1 answer
1k views

Two random variables are independent if all continuous and bounded transformations are uncorrelated.

Here's a statement I've come across multiple times but have never seen a proof of: Two random variables $X$ and $Y$ are independent, if for all continuous and bounded funtions $f, g: \mathbb R\to\...
Epiousios's user avatar
  • 3,246
4 votes
0 answers
234 views

Revision of Borel-Cantelli, $(X_n)_{n \geq 1}$ sqn of $\geq 0$ identical RVs with $E(X) < \infty$ then $X_n/n \to 0$ a.s., are my arguments correct?

I care to understand the concept behind the Borel-Cantelli Lemma better, hence I would appreciate it if someone could take the time to check if my arguments below are clear and rigorous. Statement: ...
Spaced's user avatar
  • 3,499
3 votes
0 answers
341 views

An elegant proof of monotone convergence theorem

I have found an elegant proof of monotone convergence theorem here. I represent the proof below. It's so simple that I'm afraid if I miss some subtle detail. Could you please check if my understanding ...
Akira's user avatar
  • 17.6k
1 vote
1 answer
430 views

Proof of $\operatorname{E}(u(X)) = \int_{-\infty}^\infty u(x) f(x) dx$.

I want to prove that, for any monotonous function $u$: $$\operatorname{E}(u(X)) = \int_{-\infty}^\infty u(x) f(x) dx$$ I use that $Y = u(X)$ and then use the CDF method to change variables in the ...
Alex Lostado's user avatar
1 vote
1 answer
103 views

Prove that $\lvert E[X]-m\rvert \le \sqrt{\text{var}\left(X\right)}$

I want to prove that: $$\lvert E[X]-m\rvert \le \sqrt{\text{var}\left(X\right)} $$ where $m$ is the median. My attempt: $$ \begin{aligned}&\lvert E[X]-m\rvert \le \sqrt{\text{var}\left(X\right)} \\...
qmd's user avatar
  • 4,285
1 vote
1 answer
875 views

Prove Z is a martingale by defining it is a product of random variables

Given a filtered probability space $(\Omega, \mathscr{F}, \{\mathscr{F_n}\}, \mathbb{P})$ where $\mathscr{F_n} = \mathscr{F_n}^{Z} \doteq \sigma(Z_0, Z_1, \ldots, Z_n)$, show that $Z = (Z_n)_{n \geq ...
BCLC's user avatar
  • 13.7k
0 votes
1 answer
620 views

Prove that the Extension Theorem is Complete.

Prove that the probability triple $(\Omega, \mathcal{M}, \mathbb{P^*}) $ constructed from the Extension Theorem is complete. Specifically, this problem asks us to show that, given any $A \subseteq \...
Mo Pol Bol's user avatar
  • 1,348
0 votes
1 answer
307 views

Find the probability of error of this channel

I am working on the following exercise: Let $\mathcal{C} = (\mathcal{X} , P, \mathcal{Y})$ be a channel with $\mathcal{X} = \mathcal{Y} = \{0,1\}$ and transition matrix $$ P = \begin{bmatrix}...
3nondatur's user avatar
  • 4,222
0 votes
2 answers
237 views

$\mathcal B=\sigma(\mathbb B)$ implies $f^{-1}(\mathcal B)=\sigma(f^{-1}(\mathbb B))?$

I'm having a little difficulty proving the following exercise: Suppose $(X, \mathcal A)$ and $(Y, \mathcal B)$ are two measurable spaces, and $f: X \to Y$ is measurable. Suppose also that $\mathcal B$...
syeh_106's user avatar
  • 3,145

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