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4 votes
2 answers
407 views

Relation between regularities of the trajectory of a mean zero gaussian process and its covariance operator

Let $\xi_t$ be a zero-mean gaussian process on $[0,1]$ with covariance operator $C$. I would like to better understand the relation between the covariance operator and the regularity of the ...
1 vote
1 answer
229 views

Gaussian width of intersection of cube and ball in high-dimensional euclidean space

Let $d$ be a large positive integer and fix $r \ge 0$. Set $S := B_2^n \cap [-r,r]^d$, where $B_2^d$ is the euclidean unit-ball in $\mathbb R^d$. Finally, let $\omega(S)$ be the Gaussian width of $S$, ...
4 votes
2 answers
349 views

Does the average of correlated Gaussian random variables with mean zero and different variances converge in probability to their mean?

Let $X_i\sim N(0,\sigma_i^2)$ and $\operatorname{Corr}(X_i,X_j)>0$. Is it possible to show that $$\frac{1}{N} \sum_{i=1}^N X_i \overset{p}\rightarrow E[X_i]=0.$$ Do you have a reference to a law of ...
1 vote
1 answer
318 views

How to calculate this limit (if exist)?

I have just asked the calculation of the following summation see here $$S(a,b,m,n_1,n_2)=\sum_{k=0}^m a^k b^{m-k} {n_1\choose k} {n_2\choose m-k}, $$ which is motivated by the calculation of the ...
1 vote
0 answers
83 views

Properties of max of many linear combinations of a multivariate normal vector and/or sum of top $k$ elements of a multivariate normal vector

Thank you in advance for your help! I am interested in studying the following probability: $$P\big[\max_{H \subset X,|H|=k} \sum_{i \in H} \mathbf{a}_i^T \mathbf{w} \ge 0 \big],$$ where $\mathbf{a}_i$ ...
0 votes
1 answer
82 views

WLLN for bootstrap means of stationary ergodic processes?

Setup:$\quad$ Suppose that $(X_n)$ is a stationary ergodic process with $E|X_1|<\infty$. Given $X^{(n)}=(X_1, \dots, X_n)$, select a standard Efron bootstrap subsample $(X_{n,1}^*, \dots, X_{n,m(n)}...
1 vote
1 answer
385 views

How fast does this Gaussian random walk move away from the origin?

Suppose $z_i$ are IID zero-centered $d$-dimensional Gaussian random variables with unit-trace covariance $\Sigma$ and $g(z_i)$ is the sum of its components. Consider the following random walk: $$x_s=\...
1 vote
0 answers
82 views

Concavity of expected size of a maximum matching (in a bipartite graph) w.r.t. edge probability

Given a n*n bipartite graph where each edge (between any two nodes on the opposite side) is formed i.i.d. with probability $p$, can we show a concavity result on the expected size of a maximum ...
3 votes
1 answer
210 views

Probabilistic Taylor theorem for concave functions

This paper proves a probabilistic version of Taylor's theorem \begin{equation*} \mathbb{E}g(X) = \sum_{k=0}^{n-1} \frac{g^{(k)}(0)}{k!} \mathbb{E}X^k + \frac{\mathbb{E}X^n}{n!} \mathbb{E} g^{(n)}(X_{(...
2 votes
0 answers
124 views

Rough path expected signature vs cumulant-generating function / characteristic function

What is the point of using rough path expected signature to characterize the law of а stochastic process when the cumulant generating function is known ($\log\mathbb{E}[e^{i\theta X(t)}]$)? Since an ...
3 votes
1 answer
257 views

Triangle equality for cosine similarity in high dimensions

I'm trying to understand whether I can use the following equality in my application -- for $u,v,w \in \mathbb{R}^d$: $$\cos(u,w)\approx \cos(u,v)\cos(v,w)$$ Where $\cos(x,y)$ gives cosine of the angle ...
1 vote
0 answers
59 views

How to calculate the unifrom entropy or VC dimension of the following class of functions?

When dealing with U process I meet with such a uniform entropy to calculate. For any $\eta>0$, function class $\mathcal{F}$ containing functions $f=\left(f_{i, j}\right)_{1 \leq i \neq j \leq n}: \...
3 votes
1 answer
532 views

What is a tensor product of random variables?

I am trying to understand the the following paper https://arxiv.org/pdf/1810.10971.pdf, in particular Example 2: If $ Y \sim N(0,1)$, the standard normal on $\mathbb{R}$, then $ \begin{align*} \Big( \...
4 votes
1 answer
489 views

CLT convergence rate for sum of uniforms (in TV distance)

Suppose $X_1, \cdots, X_n \sim_{\mathrm{iid}} U([-1,1])$, where $U([-1, 1])$ denotes the continuous uniform distribution over the interval $[-1, 1]$ (so $E[X_i] = 0$ and $\text{Var}[X_i]= 1/3$). Let $...
3 votes
3 answers
203 views

$\mathbf{y}=f(\mathbf{x},\mathbf{z})=g(\mathbf{x})$ if $\mathbf{z}\perp \!\!\! \perp \{\mathbf{y},\mathbf{x}\}$ jointly?

Let $\mathbf{y},\mathbf{x},\mathbf{z}$ are real-valued random vectors with possibly different dimensions. Assume $\mathbf{y}=f(\mathbf{x},\mathbf{z})$ for some function $f$. If $\mathbf{z} \perp\!\!\!\...
3 votes
1 answer
243 views

Independent input feature z can be removed: if y=f(x+z,z), then y=g(x)?

Let $y\in \mathbb{R}$ and $\mathbf{x},\mathbf{z}\in\mathbb{R}^p$ be random variable and random vectors. Assume $y=f(\mathbf{x}+\mathbf{z},\mathbf{z})$ for some function $f$. Is the following statement ...
6 votes
1 answer
527 views

Can information be extracted more precisely using more random trials?

Write $n$ iid draws of $(x,y)$ as $(x^n, y^n)$. Fix $R\in (0,H(x))$. What is the min of $n^{-1}H(y^n|f(x^n))$ over maps $f$ with range $\lbrace 1,\dots,\exp nR\}$, taking $n\to \infty$?
1 vote
1 answer
217 views

How to normalize an Inverse Wishart random matrix?

Background: Let $d\in \mathbb{N}$. Define the space of (real symmetric) positive definite matrices of size $d\times d$ as follows: \begin{align} \mathcal{S}_{++}^d := \big\{\mathbb{M}\in \mathbb{R}^{d\...
5 votes
2 answers
2k views

Relationship between KL, chi-squared, and Hellinger

There are many well-known relationships between the KL divergence, chi-squared ($\chi^2$) divergence, and the Hellinger metric. In the paper "Assouad, Fano, and Le Cam" by Bin Yu, the author ...
6 votes
0 answers
295 views

Dimension-free sample complexity for estimating Gaussian covariance

(also asked on math.se, with no answers) Suppose I have $m$ samples drawn from a Gaussian in $\mathbb{R}^n$, and need sample covariance $\Sigma_m$ to be $\epsilon$-close to true covariance $\Sigma$: $$...
1 vote
1 answer
169 views

How to prove that is a consistent estimator?

Let $\hat{\pi}^N$ be an AW-consistent estimator of $\pi$ (i.e., $\hat{\pi}^N$ is a strongly consistent estimator of $\pi$ under adapted (or called nested) Wasserstein distance $AW(\pi, \hat{\pi}^N)\to ...
1 vote
1 answer
141 views

How to get the estimator?

They introduce a new correlation. For $\pi\in \Pi(\mu,\nu)$ the set of coupling of two probability measures $\mu$ and $\nu$ on a Polish space $(X,d)$. The author introduces a plugin estimator. ...
2 votes
0 answers
139 views

Optimal Monte Carlo Trace Estimator

For a psd real symmetric $d\times d$ matrix $A$ and a function $f: \mathbb{R}^d \to \mathbb{R}$, with $f(x) := x^T A x$ we have that with $p(x) = \mathcal{N}(0_d, I_d)$ (i.e. standard multivariate ...
6 votes
2 answers
344 views

Entropy & difference between max and min values of probability mass

Let $X$ be a random variable with probability mass function $p(x) = \mathbb{P}[X = x]$. I know entropy $H(X)$ of $X$ measures the uncertainty of $X$ and a large value of $H(X)$ means $p(x)$ is nearly ...
3 votes
1 answer
614 views

An inequality relating the Kullback-Leibler divergence of two discrete distributions with constant reference distribution

Suppose that $D_{KL}(p_1\parallel q)<1$ and $D_{KL}(p_2\parallel q)<1$. I'm trying to show that either $D_{KL}(p_1\parallel p_2)$ or $D_{KL}(p_2\parallel p_1)$ will have an upper bound close to ...
0 votes
1 answer
116 views

What's the cumulative probability of these particular bags of liquorice allsorts?

After eating a bag of liquorice allsorts in one sitting, as one does, I noticed that it had contained an unusual amount of brown ones (which, you will agree, are an abomination that should never have ...
0 votes
0 answers
103 views

Does such probability distribution exist?

I'm hunting for a probability distribution with the following properties: The support is $(0,\infty)$. Denote by $F(x)$ the CDF of this distribution. If $X_1, X_2,...$ are independent random ...
1 vote
1 answer
251 views

Using Hoeffding inequality for risk / loss function

I've got a question to the Hoeffding Inequality which states, that for data points $X_1, \dots, X_n \in X$, which are i.i.d. according to a probability measure $P$ on $X$, we find an upper bound for: $...
2 votes
2 answers
709 views

Computing equivalent vector of random variables from covariance matrix

Given a covariance matrix, how can I construct a vector of expressions of randomly distributed variables whose covariance matrix is equal to the given one? EDIT: All variables are normally ...
0 votes
1 answer
108 views

On the invertibility of $Z^\top Z$, where $Z$ is a Random matrix with concentrated weakly correlated entries

Let $d$, $n$, and $m$ be large positive integers. Let $X=(x_1,\ldots,x_n) \in \mathbb R^{n \times d}$ be a random matrix iid rows from some distribition $P$ on $\mathbb R^d$ which admits a density. ...
2 votes
1 answer
936 views

Upper-bound for spectral norm of the covariance matrix of a certain Gaussian vector with correlated entries

Let $n$ and $m$ be large positive integers. Let $x=(x_1,\ldots,x_n)$ be a vector of independent random variables from $N(0,1)$. It is clear that the covariance matrix of $x$ is $I_n$, the identity ...
14 votes
8 answers
3k views

Relevant mathematics to the recent coronavirus outbreak

I would like to ask about (old* and new) reliable mathematical literature relevant to various mathematical aspects of the recent coronavirus outbreak: In particular, standard statistical/mathematical ...
3 votes
0 answers
92 views

What dynamical properties should we expect from systems satisfying statistical ones?

Some results on probability theory can be generalized to more abstract ones in ergodic theory, for example: the strong law of large numbers can be seen as a particular case of Birkhoff's ergodic ...
39 votes
3 answers
4k views

Manifold of probability measures: connections between two types of metrics

The space of probability measures could be viewed as an infinite-dimensional manifold, equipped with two possible types of metrics — (1) Wasserstein and (2) Fisher-Rao. Metric (1) is connected with ...
1 vote
0 answers
417 views

Conditions for equivalence of RKHS norm and $L^2(P)$ norm

Let $K$ be a psd kernel on an abstract space $X$ and let $H_K$ be the induced Reproducing Kernel Hilbert Space (RKHS). Let $P$ be a probability measure on $X$ such that $H_K \subseteq L^2(P_X)$ and ...
3 votes
1 answer
111 views

Distribution/moments of transformed normally distributed random vector

Let $\varepsilon \sim N\left ( 0,I_{k} \right )$, consider the following function of $\varepsilon$, $y=\left ( A+B\varepsilon \varepsilon {}'B{}' \right )^{^{\frac{1}{2}}}\varepsilon $, where $A$ is a ...
4 votes
1 answer
164 views

Limiting value of expectation of trace of exponential of Wishart matrix

Let $X$ be an $n \times d$ random matrix with iid entries from $N(0, 1/d)$. Let $S:=X^\top X/n$, a $d \times d$ Wishart matrix and let $T = e^{S} := \sum_{k=0}^\infty \dfrac{S^k}{k!}$ be its ...
3 votes
3 answers
244 views

Example of a (strictly) proper scoring rule on a general measurable space?

Most of the literature on scoring rules that I know of deals with discrete measurable spaces, but in this paper by Gneiting and Raferty a very general definition of a scoring rule is given. I don't ...
2 votes
1 answer
154 views

Random probability following a log concave distribution of order p

In the article "Concentration of the information in data with Log-concave distributions" of Bobkov and Madiman, it is written that if $X$ is a positive random variable following a log ...
0 votes
1 answer
83 views

Functional relationship between two quantities

Let $\mu \in \mathbb R^n$ and let $\Sigma$ be a positive-definite matrix of order $n \ge 2$. Fix $t \ge 0$ and define $\alpha(\mu,\Sigma,t) > 0$ by $$ \alpha(\mu,\Sigma,t) := \sup_{\|w\| = 1}\frac{...
2 votes
1 answer
84 views

Estimation of Lévy measure of ID distribution

Suppose that the positive random variable $X$ is infinitely divisible and supported on $\mathbb R_+$. Due to Lévy-Khintchine, its moment generating function then writes : $$M(t) = \mathbb E\left(e^{tX}...
3 votes
2 answers
169 views

On finding an upper bound on the error of a sparse approximation

I posted this question on math.stackexchange earlier, but didn't see any response. So, I am posting it here, in case someone else has an answer. Original question: https://math.stackexchange.com/...
2 votes
0 answers
61 views

Approximate logarithmic bound on expected maximum via central limit theorem

If $Z_i$ are standard normal, possibly dependent, one can show that $$E\left[\max_{i=1,...,M} Z_i^2\right]\leq 3\ln M + 1.$$ I'm looking for a similar (asymptotic) bound for asymptotically normal ...
1 vote
1 answer
259 views

Non-independent Sub-gaussian variables and concentration

Let $g \in R^{d}$ have $iid$ Gaussian components. Let $a \in R^{d}$, and let $b \in R^{d}$. be arbitrary vectors. Consider the random variable $Y_{g,g}:= \frac{1}{n}\langle g,a \rangle \langle g, b \...
9 votes
2 answers
636 views

Induction arising in proof of Berry Esseen theorem

I've been studying the paper An estimate of the remainder in a combinatorial central limit theorem by Bolthausen, which proves the Berry Essen theorem using Stein's method: Let $\gamma$ be the ...
0 votes
0 answers
36 views

How to recalculate the weights for an event that happens multiple times and requires all outcumes to be unique?

I think it's easiest to explain with an example. I have a weighted probability list A : 0.15 B : 0.15 C : 0.15 D : 0.1 E : 0.1 F : 0.1 G : 0.1 H : 0.075 I : 0.075 ...
3 votes
1 answer
271 views

For a random sequence $X_0, X_1, X_2, \ldots$ and $F_n$ the empirical CDF, does $F_n(X_0)$ converge to a uniform random variable?

Let $X_0, X_1, X_2, \ldots$ be a sequence of i.i.d. real-valued random variables on some probability space $(\Omega, \mathcal{F}, \mathbb{P})$ with continuous CDF $F(x)$ and define a sequence of ...
0 votes
0 answers
97 views

Verification of a certain computation of VC dimension

Disclaimer: I'm not very familiar with the concept of VC dimensions and how to manipulate such objects. I'd be grateful if expects on the subject (learning theory, probability), could kindly proof ...
10 votes
2 answers
2k views

Convergence of an empirical distribution w.r.t. the Hellinger distance

Let $P$ be a probability distribution on a finite set $\mathcal{X}$ and let $X_1, X_2, \ldots, X_n$ be drawn i.i.d. according to $P$. Define the empirical distribution: $\hat{P_n}(x) = \frac{1}{n} \...
3 votes
1 answer
845 views

Concentration inequality for the sample covariance matrix

I'd like to know if there is a concentration inequality for the sample covariance matrix that don't assume the knowledge of the true mean. Background. Given a probability distribution $\mu$ on $\...

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