0
votes
1answer
22 views

Probability densities and Absolute continuity

I've not deep knowledge in measure theory/real analysis but just few concepts given me during this second year probability course. I'm trying by myself to understand more, but I don't want to dive in ...
4
votes
2answers
129 views

A counter example of Brownian Motion

Here is an example in my textbook to illustrate why we need the continuous sample path in the definition of Brownian motion. Let $(B_t)$ be a Brownian motion and $U$ be a uniform random variable on ...
2
votes
1answer
21 views

Filtration from a Brownian Motion

The textbook I am reading defines the filtration induced from a Brownian Motion as follows. Let $\{B(t): t \geq 0\}$ be a Brownian Motion defined on some probability space, then we can define a ...
-6
votes
0answers
42 views

NUMBER OF ATOMS IN A SIGMA-ALGEBRA [on hold]

I have been trying to solve the followIng question. DESCRIBE THE SMALLEST SIGMA ALGEBRA CONTAINING 'n' ARBITRARY SUBSETS OF THE SAMPLE SPACE.GIVE AN UPPER BOUND FOR THE NUMBER OF SETS IN THIS SIGMA ...
2
votes
1answer
49 views

Relation between uniformly distributed random variable and i.i.d Bernoulli sequence (Cantor space)

(Uniform RV <==> i.i.d Bernoulli sequence) (1) Let $(X_n)_n$ be a sequence of i.i.d. Bernoulli random variables($P(X_n=0)=P(X_n=1)=\frac 12$) on a probability space. Then show that $\xi:= \sum_n ...
2
votes
1answer
69 views

Conditional probability explained?

Let $F_A$ be the CDF to the random variable $A$ ( and $B$ another independet rv), how do we get that $P(A+B \le s) = \int_{\mathbb{R}} P(A+B \le s\mid A=x ) \, dF_A(x)$ (This is probably a ...
2
votes
1answer
24 views

Absolutely continuous probability measures example

I was given the following definition: Then this example: It is said that $\mathbb P_1\ll\mathbb P_2$ , but I don't really see it.Please help.
2
votes
2answers
62 views

From distribution to Measure [duplicate]

I have been asked to create a new post with my question. So it is about starting from a distribution function and proving that we can always find a probability space. My attempt is this : So assume ...
1
vote
0answers
29 views

From distribution function to probability measure

So assume we have a probability space $(\Omega, \mathcal{F}, P)$ and a random variable $X : \Omega \rightarrow \mathbb{R}^*$. We can derive from this a distribution $P_X$, and a distribution function ...
1
vote
1answer
32 views

Measurability of a Borel function

I need some help on the following proof. The claim is: Suppose $f:\mathbb{R}^k \to \mathbb{R}$ and $f \in B(\mathbb{R}^k)/B(\mathbb{R})$. i.e. Borel measurable. Let $X_1$,...,$X_k$ be random ...
1
vote
1answer
58 views

Let F be a distribution function. Prove that X is a RV.

Let F be a distribution function. On $(\Omega, \mathfrak{F}, P)=((0,1), \mathfrak{B}(0,1),\lambda)$ where $\lambda$ denotes Lebesgue measure. Define X: $\Omega \ to \mathbb{R}$ by $X(\omega) = sup(y ...
0
votes
2answers
60 views

If a probability space has no measurable subsets with $P$ strictly between $0$ and $1$, then every random variable is constant a.s.

Let $(\Omega, \mathfrak{F}, P)$ be a probability space such that $\forall F \in \mathfrak{F}, P(F) = 0 \ or \ 1$. Show that for all random variables X on $(\Omega, \mathfrak{F}, P)$, $\exists \ c ...
1
vote
2answers
56 views

If X and Y are random variables with the same distribution, prove that f(X) and f(Y) are random variables that have the same distribution.

Suppose X is a RV on $(\Omega, \mathfrak{F}, P)$. Let f be Borel-measurable on $(\mathbb{R}, \mathfrak{B})$. 1 Show that f(X) is also a RV on $(\Omega, \mathfrak{F}, P)$. 2 Let Y ba RV on ...
1
vote
0answers
28 views

The projective limit of probability spaces and the Kolmogorov-Daniell theorem

Does the "projective limit" concept exist for probability spaces? The only result that I know of seems to be the Kolmogorov-Daniell theorem, but this is just a particular case where the spaces ...
0
votes
1answer
42 views

An example of stochastic process

I use the following definition for a stochastic process. Let $(\Omega, \mathcal F, P)$ be a probability space, $(E, \mathcal E)$ be a measurable space, and $T$ be a non-empty set. A collection ...
1
vote
1answer
32 views

$F_n \overset{w}{\to} F$, and $F$ is continous. Show that $F_n$ converges to $F$ uniformly on $\mathbb{R}$

$\{F_n\}$ and $F$ are distribution functions, and $F$ is continuous on $\mathbb{R}$. If $F_n$ converges weakly to $F$, show that $$ \sup_x | F_n(x) - F(x) | \to 0, n \to \infty $$ I know that ...
1
vote
0answers
33 views

Show that the series $\sum\limits_n P(A \cap A_n)$ converges for $A=\bigcap\limits_{n=M}^{\infty} A_n^{c}$. [duplicate]

Show that the series $\sum\limits_n P(A \cap A_n)$ converges for $A=\bigcap\limits_{n=M}^{\infty} A_n^{c}$. From here http://math.stackexchange.com/a/878635/140308 (proof attempt is there too) Sorry ...
1
vote
1answer
30 views

$\sigma(X_1,\dots, X_n) = \sigma(S_1,\dots, S_n)$ generated by partial sums

is true that $\sigma(X_1,\dots, X_n) = \sigma(S_1,\dots,S_n)$ where $S_n=\sum_{i=1}^n X_i$ in general or I have to impose additional restrictions to the random variables (for instance, independence)? ...
3
votes
0answers
64 views

Why not defining a measure as a function on functions?

A measure $\mu$ is a function to $\left[0,\infty\right]$ on the sets belonging to a $\sigma$-algebra. Then for integrable functions $f$ the integral $\int fd\mu$ comes in, having nice properties ...
1
vote
0answers
21 views

Integration respect the Lévy measure

How I can compute numerically $$\int_{a}^{b}f(z)\nu(dz)$$ where $\nu$ is a Lévy measure and $f$ is a continuous function? Is it equivalent to $$\int_{a}^{b}f(z)d\nu(z)$$ Thanks
0
votes
1answer
59 views

$P(\limsup A_n)=1 $ if $\forall A \in \mathfrak{F}$ s.t. $\sum_{n=1}^{\infty} P(A \cap A_n) = \infty$

Let $\mathfrak{F} = (A_n)_{n \in \mathbb{N}}$. Prove that $P(\limsup A_n)=1$ if $\forall A \in \mathfrak{F}$ s.t. $P(A) > 0, \sum_{n=1}^{\infty} P(A \cap A_n) = \infty$. (Side question 1 Is second ...
3
votes
0answers
22 views

Ultrametric space of stochastic filtration

Let $\Omega$ be an arbitrary set and $(\mathscr F_t)_{t\in \Bbb R_+}$ be a non-decresing sequence of $\sigma$-algebras on $\Omega$ such that any subset of $\Omega$ is contained is some of them, that ...
2
votes
0answers
10 views

Pushfoward of measures Lipschitz continuous in total variation

Let $X,Y$ and $Z$ be metric spaces and $f:X\times Y\to Z$ be a measurable map. Suppose that we are given a probability measure $\mu$ on $Y$, and define a stochastic kernel $$ ...
2
votes
1answer
34 views

Calculating difference between two probability distributions.

What is a good measure of the difference between two probability distributions other than Kullback–Leibler divergence?
3
votes
1answer
33 views

Local convexity of the topology of weak convergence of probability measures

Let $X$ be a Polish or standard Borel space, and $\mathcal P(X)$ be the space of all Borel probability measures on $X$ endowed with the topology of weak convergence. I am thinking of using ...
1
vote
1answer
33 views

Proving and visualizing $\mathbf 1_{(x,x+a]}(y) = \mathbf 1_{[y-a,y)}(x)$

Here is a trick from one of the proofs in probability: $$\iint \mathbf 1_{(x,x+a]}(y) \ \lambda(dx) \ \mathbb P(dy) = \iint \mathbf 1_{[y-a,y)}(x) \ \lambda(dx) \ \mathbb P(dy)$$ for $a>0$. So ...
3
votes
1answer
81 views

Usual convex combination and the one with measure

Let $X$ be a Borel measurable subset of $\Bbb R^n$ and let $\nu$ be a probability measure on $X$. Can we always find an integer $m$, points $x_1,\dots,x_m\in X$ and coefficients $a_1,\dots,a_m \geq ...
3
votes
1answer
73 views

Extensions of universal measures

Let $(\Omega,\mathcal F)$ be a measurable space, and let $\mathcal P$ be the set of all probability measures no this space. Let $\mathcal F^p$ denote a completion of $\mathcal F$ w.r.t. $p\in P$ and ...
1
vote
1answer
44 views

Space of Gaussian Functions is Closed in $L^2$

Let $\Omega, \mu$ be a probability space. A measurable function $f: \Omega \rightarrow \mathbb{R}$ is called Gaussian if $$\mu (f^{-1}(A))=\frac{1}{\sigma \sqrt{2\pi }}\int_Ae^{-x^2/2\sigma ^2} dx$$ ...
1
vote
0answers
33 views

The completed natural filtration of brownian motion is right-continuous, proof?

I have a question concerning a claim in J.F. LeGall's book Mouvement brownien, martingales et calcul stochastique. Let $(\mathcal{F_{t}})$ be the canonical completed filtration on $\Omega$ of a real ...
2
votes
2answers
49 views

Can any measure be made into a bounded measure?

Is it possible to derive a bounded measure from any measure on a measure space? For example can the Lebesgue measure be made into a probability measure?
1
vote
0answers
41 views

Linear w.r.t. any measure

Let $X$ be a Banach space endowed with a Borel $\sigma$-algebra. How do we call a real-valued Borel function $f$ that satisfies for any Borel probability measure $\mu$ the following formula $$ ...
1
vote
0answers
28 views

Proving $\sigma$-additivity and interchanging order of summation/integration just because positive

Prove $\sigma$-additivity in the ff: Let $\Omega = {\omega_1, \omega_2, ...}$ be some countable set. Let $\mathfrak{F} = 2^{\Omega}$. Consider a sequence {$p_n$} in [0,1] s.t. $\sum_{n=1}^{\infty} ...
1
vote
0answers
47 views

Representation of a linear functional Lipschitz in total variation

Let $\Omega$ be a Borel space and let $\mathcal P(\Omega)$ be the space of all Borel probability measures on $\Omega$ endowed with the topology of weak convergence. Define the total variation metric ...
2
votes
1answer
60 views

Intuition in probability theory

Good afternoon. Could you please suggest me some books or may be articles where I can read about the intuition of Kolmogorov's axiomatics. I know it, I can solve university problems but I can't feel ...
0
votes
1answer
36 views

Measurability and knowledge

there seems to be a subtle relationship between knowledge and measurability. If I have a stochastic process $(X_n)_n$, then for example a stopping time ( other examples would be martingales, ...
2
votes
1answer
25 views

Convergence in total variation

There are the very basic convergence types in probability theory: almost sure, in $L^p$-norm, in measure and in distribution. Besides that there is the concept of convergence in total variation norm. ...
0
votes
1answer
40 views

Find $\liminf X_n$ where $X_n=1_{[n,n+1]}$?

My attempt: Suppose $\omega=n_0$. Then choose $N\geq n_0+1$.Threfore, $X_N(\omega)=0$. Therefore, $\inf_{k\geq N}X_k(\omega)=0$. Does it suffice to prove that $\liminf\limits_{n \rightarrow \infty} ...
1
vote
1answer
20 views

Prokhorov-like convergence

Let $(X,d)$ be a metric space, and for any $A\subseteq X$ define $$ A^\delta:=\{y\in X:\exists x\in A \text{ such that }d(x,y)\leq \delta\}. $$ Under which conditions on $(X,d)$, $A \subseteq X$ and ...
0
votes
1answer
31 views

Wasserstein metric: conditions for the existence of minimizer and duality

Let $(X,d)$ be a metric space and let $\mathcal P(X)$ be the set of all Borel probability measures on $(X,d)$. The Wasserstein distance on $\mathcal P(X)$ is given by $$ W_d(\mu,\bar\mu):=\inf_{M\in ...
1
vote
0answers
53 views

$X_n=n^21_{(0,1/n)}$. What is $\limsup\limits_{n \rightarrow \infty} X_n$

$X_n=n^21_{(0,1/n)}$. What is $\limsup\limits_{n \rightarrow \infty} X_n$? What about its $\liminf\limits_{n \rightarrow \infty} X_n$? My attempt: For each $n$ on $\{0, [1/n,1]\}$, we have ...
1
vote
0answers
38 views

Prove that E$(\liminf\limits_{n\rightarrow \infty} X_n )\leq \liminf\limits_{n\rightarrow \infty}E(X_n)$

I want to prove that if $X_n\geq 0$, then E$(\liminf\limits_{n\rightarrow\infty} X_n )\leq \liminf\limits_{n\rightarrow\infty}E(X_n)$. My attempt: $E(\liminf\limits_{n \rightarrow \infty} ...
1
vote
1answer
26 views

convergence in measure of min $(f_n,g)$

I was reading a proof of a convergence in measure variant of fatou's lemma earlier and there was a seemingly easy part of it I just could not verify. Assume $(f_n)_{n \in \mathbb N}$ is a sequence of ...
1
vote
1answer
25 views

Almost Trivial $\sigma-$fields

I am trying to understand the proof of the following Lemma form the book A probability path by sidney Resnick. Lemma: Let $\mathcal{G}$ be an almost trivial $\sigma-\text{field}$ and let $X$ be a ...
1
vote
2answers
43 views

Show that the shift map is measurable and measure-preserving

Show that the shift map $\theta$ of Definition 6.3 is measurable and measure-preserving. Not sure how to represent $\theta^{-1}$ which I believe is where I am stopped in solving this problem.
0
votes
1answer
72 views

How to make sense out of this: Ergodic theorem for Markov chains

We had the ergodic theorem for Markov chains, stating that: For a state space $S \subset \mathbb{N}$ and all functions $f \in L^1$ (meaning that $\sum_{s \in S} |f(s)|\pi(s) < \infty$) and an ...
2
votes
1answer
38 views

law of iterated logarithm

Wikipedia claims see this link that the law of the iterated logarithm marks exactly the point, where convergence in probability and convergence almost sure become different. It is apparent from the ...
0
votes
1answer
24 views

Convergence in Probability implies Weak Convergence Proof Question

I'm trying to follow a proof for showing $\displaystyle \lim_{n\rightarrow \infty} P[|X_n-X|>\epsilon] = 0 \Rightarrow X_n \rightarrow_p X$ The first step of the proof says: $P[X \leq x-\epsilon] ...
4
votes
0answers
46 views

A formula similar to $\int_a^bf(x)dx=\mu\left[a,b \right]$ for $f^p$.

Let $\mu$ be an absolutely continuous measure with respect to the Lebesgue measure on $\mathbb{R}$ , and $f:\mathbb{R}\to \mathbb{R^+}$ its Radon-Nikodym derivative . We can write $\int_a^bf(x)dx$ in ...
1
vote
1answer
30 views

Simulation of a random vector

I have a question which is probably well known but I do not find any written reference. Let us consider a probability measure $\mu$ on $\mathbb{R}^2$. I would like to know if one can find a random ...