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Which results in probabilistic group theory generalize from finite groups to compact Hausdorff groups (and which don't)?

Let $G$ be a finite group. It has been shown that: If the probability that two randomly selected elements of $G$ generate an abelian group is greater than $5/8$, $G$ is abelian. If the probability ...
ckefa's user avatar
  • 495
11 votes
0 answers
381 views

Concerning Luzin-(N)-property

Definition: a function $f:\mathbb{R}\to \mathbb{R}$ has Luzin-(N)-Property if $f$ maps any null set to a null set. By https://www.encyclopediaofmath.org/index.php/Luzin-N-property, it is known that ...
喻 良's user avatar
  • 4,201
10 votes
0 answers
338 views

Simultaneous strong law of large number classes?

Say that $C$ is a SSLLN class of subsets of some Polish space $V$ provided that for every sequence of Borel i.i.d.r.v.s $X_1,X_2,...$ with values in $V$, we almost surely have: For every $A$ in $C$, $\...
Alexander R Pruss's user avatar
9 votes
0 answers
223 views

Cramer's theorem in Hilbert spaces

I am interested under what conditions Cramer's theorem applies in random variables taking values in Hilbert spaces. Following these lecture notes, but using a Hilbert space: Let $X_1,X_2,\cdots$, be ...
Manuel Schmidt's user avatar
8 votes
0 answers
422 views

Non-affine smooth transformation of Gaussian is Gaussian

Suppose $Z\sim N(0,1)$ (standard Gaussian) and $f: \mathbb{R} \to \mathbb{R}$ is a differentiable function such that $f(Z)\sim N(0,1)$. My question is whether there exists any such $f$ other than $f(x)...
De vinci's user avatar
  • 399
8 votes
0 answers
212 views

Qualitative weakenings of probabilistic independence

In probability theory, independence of random variables is characterised by $$(1)~~X~\text{independent}~Y \; \iff \; P_{(X,Y)} = P_X \otimes P_Y \enspace ,$$ where $P_{(X,Y)}$ is the joint probability ...
Alex Simpson's user avatar
8 votes
0 answers
729 views

Density of countably additive measure in the set of all finitely additive measures.

Let $S$ be a countable discrete set, the following two results are quite easy to prove: Every countably additive probability measure $\mu$ on $S$ commutes (in Fubini's sense) with every finitely ...
Valerio Capraro's user avatar
7 votes
0 answers
169 views

Relationship between measure theory and quantification

I was advised that this question might be better suited for mathoverflow, so I am reposting it here (original post). In a 1978 paper published by David P. Ellerman and Gian-Carlo Rota, the duo discuss ...
John Smith's user avatar
7 votes
0 answers
549 views

Counter-example to the completeness of the Wasserstein metric

$\newcommand{\P}{\mathcal{P}}$ Let $(E,d)$ be a complete metric space, let $\P(E)$ be the set of all probability measures on $(E,\mathcal{B}(E))$. Let $W_d$ be the $1$-Wasserstein (Kantorovich) ...
Oleg's user avatar
  • 931
7 votes
0 answers
3k views

What is vague convergence and what does it accomplish?

For convenience, let's say that I have a locally compact Hausdorff space $X$ and am concerned with probability measures on its Borel $\sigma$-algebra $\mathcal{B}(X)$. Natural vector spaces to ...
Greg Zitelli's user avatar
  • 1,124
6 votes
0 answers
197 views

Prokhorov's theorem for countably many random measures on a Polish space

I am looking for help to show the following lemma: Lemma Let $(\Omega,\mathcal A,\mathbb P)$ be a complete, standard Borel probability space and $\mathcal X$ a Polish space. Let $\mathcal P(\mathcal ...
Pierre-François Massiani's user avatar
6 votes
0 answers
388 views

Closedness of a set of measures, where conditional marginals are in closed $\varepsilon$-ball w.r.t. Wasserstein distance

Let $(E,d)$ be a bounded polish space (separable, complete metric space satisfying $\sup_{x,y\in E} d(x,y) < \infty$). By $\mathcal{P}(E)$ we denote the space of Borel probability measures on $E$ ...
Steve's user avatar
  • 1,095
6 votes
0 answers
301 views

Generating stationary, ergodic random fields on a homogeneous space

Consider a homogeneous space $M$, which for the sake of concreteness, let's take to be $M = \mathbb R^d$. Fix some space $A$, and consider the space of functions $X = C(M,A)$, along with its Borel $\...
Tom LaGatta's user avatar
  • 8,512
5 votes
0 answers
266 views

Concentration inequalities for random measures

For random variables $X_1,\dots,X_n$ with common mean $\mathbb{E}[X_i]=\mu$ and common bounds $a\leq X_i\leq b$, we have the very useful Hoeffding's inequality: $$\mathbb{P}\left(\left|\mu -\frac1n\...
Tyler6's user avatar
  • 101
5 votes
0 answers
135 views

Criteria for tightness of Gaussian measures on Banach spaces

In Bogachev's book "Gaussian Measures" (Example 3.8.13) sufficient conditions for the (uniform) tightness of a sequence of centered Borel Gaussian probability measures on a separable Hilbert ...
S.Z.'s user avatar
  • 505
5 votes
1 answer
774 views

Question/References on the Skorokhod M1 topology

Let $D(0,T)$ be the space of right continuous functions with left limits defined on $[0,T]$. Consider the Skorokhod M1 topology on $D(0,T)$, see e.g. S. Ledger, Skorokhod’s M1 topology for ...
user avatar
5 votes
0 answers
332 views

Points of continuity of Kullback-Leibler divergence with respect to weak convergence

I know that the Kullback-Leibler $D(\mu||\nu) := - \int_K\log\big(\frac{d \nu}{d \mu}\big) \, d\mu,$ over probability measures on a compact $K$ subset of $\mathbb{R}^d$, is only weakly lower ...
thegain's user avatar
  • 51
5 votes
0 answers
696 views

Cadlag and adapted (usual conditions assumed) imply progressively measurable (related to Protter's Stochastic Calculus theorem 6)

Hi maybe someone on here can help me. I have been stuck on showing this fact for several months. I asked this question in the stack exchange and it has floated around for a while but to no avail. ...
Ceeerson's user avatar
  • 151
5 votes
0 answers
178 views

Support of a Measure with Characteristic Functional Continuous in $L_p$, $1\leq p <2$?

Let $\mathcal{S}(\mathbb{R})$ be the space of smooth and rapidly decaying functions and $\mathcal{S}'(\mathbb{R})$ its dual, the space of tempered distributions. Let $\mathscr{P}$ be a probability ...
Goulifet's user avatar
  • 2,306
5 votes
0 answers
137 views

Large Deviations: Exponential decay in normed spaces

Let $(X_1,X_2,\cdots)$ be a sequence of independent and identically distributed random variables taking values in some general normed space $(V,||\cdot||)$. Denote $\mu=E[X_1]$ and $S_n=\frac{1}{n}[...
Manuel Schmidt's user avatar
5 votes
0 answers
597 views

Skorohod theorem (weak convergence) on a discrete setting

I have a question about the application of Skorohod representation theorem. The questions arises in this paper about robust hedging in mathematical finance. It is about the very last equation on page ...
hulik's user avatar
  • 51
5 votes
0 answers
360 views

Existence of an universally measurable pullback

Let $X,Y$ and $Z$ be standard Borel spaces: topological spaces homeomorphic to Borel subsets of complete separable metric spaces. Let $K\subseteq X\times Y$ be analytic. Assume that $K_x$ is not ...
SBF's user avatar
  • 1,655
5 votes
0 answers
200 views

Diffusion processes in wide generality

It is common knowledge among schoolchildren that one may define jump diffusion processes in wide generality. Hard question: What are the most general structures on which one may define something ...
Tom LaGatta's user avatar
  • 8,512
5 votes
0 answers
369 views

Independent Events Inducing Probability Measures

Let $\mathcal{F}$ be a sigma algebra over $\Omega$ and $M$ the set of all probability measures on $\mathcal{F}$. Let $\mathcal{C}$ be some collection of pairs $(A,B)$ with $ \ A,B\in\mathcal{F}$. Now ...
Alex R.'s user avatar
  • 4,952
5 votes
0 answers
537 views

Conditional probabilities in Banach spaces

This is the infinite-dimensional sequel to my question, Conditional probabilities are measurable functions - when are they continuous?. Let $\Omega = \Omega_1 \times \Omega_2$ be a probability space ...
Tom LaGatta's user avatar
  • 8,512
5 votes
1 answer
363 views

Inverse marginal property of a collection of $\sigma$-algebras

In my paper "On the inverse best approximation property of systems of subspaces of a Hilbert space" I introduced the Inverse marginal property (IMP) for a collection of $\sigma$-algebras. Let $(\...
Ivan Feshchenko's user avatar
4 votes
0 answers
198 views

When a null uncountable set can be image of some increasing function with discontinuities on a dense countable set

Consider the following result: A: Let $f:D \to \mathbb R$ be an increasing function with discontinuities on a dense countable subset of $D$ such that the jump values sum to $\mu(D)$, where $D$ is a ...
Amir's user avatar
  • 303
4 votes
0 answers
119 views

Is the range of a probability-valued random variable with the variation topology (almost) separable?

Let $X$ and $Y$ be uncountable Polish spaces, $\Delta(Y)$ be the space of Borel probability measures on $Y$ endowed with the Borel $\sigma$-algebra induced by the variation distance, and let $g:X\to \...
Michael Greinecker's user avatar
4 votes
0 answers
166 views

Does the existence of regular conditional measure follow from that of regular conditional distribution?

For more succinct description, I use the following abbreviations, i.e., RCPD: Regular conditional probability distribution. RCPM: Regular conditional probability measure. First are definitions 10.4....
Analyst's user avatar
  • 657
4 votes
0 answers
492 views

Disintegration of measures: a confusion about an existence proof from a lecture note

I'm reading a proof of Theorem 2.25 below from this note. First, we recall a definition and a theorem, i.e., Theorem 2.25 (Disintegration). Let $\left(Z, d_Z\right)$ and $\left(X, d_X\right)$ be ...
Analyst's user avatar
  • 657
4 votes
0 answers
160 views

Can we show equivalence of two distributions based on their statistics?

Let $p,q$ be two distributions on $\mathbb{R}^d$. Let $f:\mathbb{R}^d\times\mathbb{R}^d\rightarrow\mathbb{R}$. Under what conditions does $\mathbb{E}_{x\sim p}f(x,z)=\mathbb{E}_{x\sim q}f(x,z)\ \...
Zhifeng Kong's user avatar
4 votes
0 answers
756 views

Tangent space and gradient on subspace of Wasserstein space given by finitely supported measures

Let $\mathcal{P}_2(M)$ be the 2-Wasserstein space over some Riemannian manifold $(M,g)$ (connected, complete, and without boundary). Let $\mathcal{FP}_2(M,n)$ be the subspace of probability measures ...
S.Surace's user avatar
  • 1,675
4 votes
0 answers
2k views

Does rate of convergence in probability come from a metric?

In general, when we talk about convergence of a sequence, we need a topological space. If we want to talk about a rate of convergence, we need to quantify how far away one element of the sequence is ...
Froomfondel's user avatar
4 votes
0 answers
358 views

Lipschitz kernel

We consider the following probability measure on $\mathbb{R}^2$: $\mu = Leb\vert_{[0,1]} \times \delta_0$. Furthermore the following dilation, say $d$, is defined as $(x,0) \mapsto \frac{1}{2}(\delta_{...
tubmaster's user avatar
  • 141
4 votes
0 answers
95 views

Approximating martingales given marginal distributions

Let $(\mu_0,\mu_1)$ be a vector of probability measures on $\mathbb R$ that are of finite first moment, i.e. $$\int_{\mathbb{R}}|x|\mu_i(dx)~<~+\infty \mbox{ for } i=0,1$$ and increasing in ...
CodeGolf's user avatar
  • 1,835
4 votes
0 answers
1k views

Total variation and Hellinger distance inequality between truncated Gaussians

We know that the total variation distance, $d_{TV}(P,Q) = \frac{1}{2}\left|\left|P-Q\right|\right|_1$, between any two distributions $P$ and $Q$ is lower bounded by their squared Hellinger distance, $...
Alexander's user avatar
4 votes
0 answers
309 views

Conditional expectation with respect to random closed sets

Short question If $X$ is a random closed set, and $Y$ is an integrable random variable, I would like a definition of the "conditional expectation" $$\mathbf{E}[Y \mid X\ni x].$$ Has this been worked ...
Jason Rute's user avatar
  • 6,287
4 votes
0 answers
233 views

Convergence of probability measures on a generating field of a sigma-field

Let $(\Omega,\mathcal{B})$ be a measurable space and let $\mathcal{F}$ be a generating field of $\mathcal{B}$. Assume $\mathcal{F}$ is standard, i.e. it is countable, and any normalized, non-negative, ...
Wei Mao's user avatar
  • 51
4 votes
0 answers
296 views

Weak*-continuity of regular conditional probabilities "in time"

Let $(\Omega, F, (F_t)_{t\geq 0}, \mathbb{P})$ assume that $(X_t)_{t\leq T} $ is some cadlag, real valued stochastic process, not too bad: say something like a Brownian Motion and some Poisson finite ...
Pierre's user avatar
  • 278
4 votes
0 answers
867 views

For what sub-$\sigma$-algebra are these two measures equivalent?

In two statistics papers (linked inline below) I have come across two definitions of certain probability measures. I conjecture that for particular choices of the construction that they are ...
R Hahn's user avatar
  • 2,791
3 votes
0 answers
130 views

A Talagrand inequality for the supremum of partial sums over function classes under dependence. (Reference request)

As a consequence to the Talagrand concentration inequality, it is well known that for a measurable space $(S,\mathcal{S})$ and an i.i.d. sample $X_1,...,X_n$ of $S$-valued random variables, if $\...
Daan's user avatar
  • 141
3 votes
0 answers
145 views

What is an example of a non-tight probability measure?

Billingsley (Convergence of Probability Measures, 1968) and van der Vaart and Wellner (Weak Convergence and Empirical Processes, 2023) discuss the concept of tight probability measures and use the ...
cgmil's user avatar
  • 277
3 votes
0 answers
45 views

Small deviation asymptotics for sub-gaussian diffusions in dirichlet spaces

Let $(X,d,\mu)$ be a metric measure space equipped with a strongly local, regular Dirichlet form $(\mathcal{E}, \mathcal{D}(\mathcal{E}))$ on $L^2(X,\mu)$. Assume that the associated heat kernel $p_t(...
Thomas Frenkel's user avatar
3 votes
0 answers
79 views

Continuity of disintegrations in non locally compact spaces

Let $X$ and $Y$ be Radon spaces, $\mu$ a Borel probability measure on $X$, $F\colon X\to Y$ measurable. Then the disintegration theorem gives us a disintegration $\{\mu^y\}_{y\in Y}$ of $\mu$ with ...
Nathaël's user avatar
3 votes
0 answers
145 views

Eigenvalues of random matrices are measurable functions

I have read that if a random matrix is hermitian then its eigenvalues are continuous, hence also measurable. If the random matrix is not hermitian, the eigenvalues are not continuous in some cases. ...
Curtis74's user avatar
3 votes
0 answers
175 views

Any reference on Jensen inequality for measurable convex functions on a Hausdorff space?

I asked this question on math.stackexchange and I was suggested that asking it may be more appropriate. This is part of my research which tries to extend some of Choquet's theory to some non-compact ...
P. Quinton's user avatar
3 votes
0 answers
179 views

Probability terminology

This is strictly a low-level terminology question. If I have a probability space $\Omega$ and a measurable space $S$, then a random variable $X:\Omega\rightarrow S$ gives rise via pushforward to a ...
Steven Landsburg's user avatar
3 votes
0 answers
77 views

Reference Request: Is every interval-valued probability measure consistent?

Short version: Does every interval-valued probability measure contain a conventional probability measure? I have a sense that this is a basic result about an obscure topic but I am having trouble ...
Owen Biesel's user avatar
  • 2,356
3 votes
0 answers
232 views

Research-type questions in probability illustrating measure-theoretical techniques for students

In short, in the perspective of preparing a new course, I am looking for examples of "concrete" (hopefully research-type) questions concerning various models in probability theory which give the ...
Gagar's user avatar
  • 406
3 votes
0 answers
198 views

Cardinality of extreme points of finitely additive probabilistic extensions

Let $\Omega = \{0,1\}^\mathbb{N}$, let $\mathcal{A}$ be the algebra generated by the open subsets of $\Omega$, where we use the product of discrete topologies, and let $\mathcal{F} = \sigma(\mathcal{A}...
aduh's user avatar
  • 869

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