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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 ...
colin's user avatar
  • 143
1 vote
0 answers
197 views

Weak convergence of Cesaro means of weakly converging infinite-dimensional distribution

Suppose we have sequences of random variables $\{X_{n,m},n \in \mathbb{N}\}$ where the distribution of $(X_{n,m})_{n\in\mathbb{N}}$ converges weakly to an infinite-dimensional normal distribution $\...
moe.dancer's user avatar
2 votes
1 answer
256 views

About a mixture

Consider the following mixture model for a univariate density function $$ (1) \quad f(x)=\int_{(m, \sigma^2)\in D} g(x; m, \sigma^2) \mu(d(m, \sigma^2)) $$ where $D$ is a compact subset of $\mathbb{R}\...
Star's user avatar
  • 108
1 vote
1 answer
126 views

Probabilistic lower and upper-bounds for a certain random quartic form involving gaussian random matrices

Let $d,m \to \infty$ (integers) with $m/d \to \rho \in (0, \infty)$. Let $C$ be a $d \times d$ psd matrix with $trace(C)=\mathcal O(1)$, and let $w_1,\ldots,w_m$ be iid uniformly distributed on the ...
dohmatob's user avatar
  • 6,853
0 votes
1 answer
209 views

Factorisation of Gaussian random matrix into random Hermitian and correction factor

By the Bartlett decomposition, one has that for $k \leq n$ and $\mathbf{\Gamma}_{n\times k} \in \mathbb{R}^{n\times k}$ a standard Gaussian matrix with independent entries $$\mathbf{\Gamma}_{n\times k}...
user avatar
1 vote
1 answer
140 views

Does a sequence that verifies the assumptions of a square integrable martingale on some event need to be convergent on this event?

I came across this claim by reading some literature on stochastic approximation. Let $(\Omega, \mathcal{A}, \mathbb{P}$) be a probability space, $(\mathcal{F}_n)$ a filtration on it. Let $(\epsilon_{n}...
J. Doe's user avatar
  • 115
1 vote
0 answers
489 views

Can we generalize the concept of "characters" in group theory via methods from statistics and probability theory?

$\DeclareMathOperator\Cov{Cov}$Motivation: If $G$ is a finite group and $\phi=X+iY: G\to \mathbb{T}$ is a character of $G$, then $\Cov(X,Y)=0$ where $X$, $Y$ are considered as two real random ...
Ali Taghavi's user avatar
0 votes
0 answers
202 views

$|\frac{1}{n}\sum_{i=1}^n X_i-E(X_1)|=O_P(\frac{1}{\sqrt{n}})$ under $E(|X_1|)<\infty$?

For i.i.d. random variables $X_1,\dots, X_n$ with $E(|X_1|)<\infty$. Does the following equation hold? $$ \left|\frac{1}{n}\sum_{i=1}^n X_i-E(X_1)\right|=O_P\left(\frac{1}{\sqrt{n}}\right) $$ I ...
John's user avatar
  • 193
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 $\Sigma$: $$...
Yaroslav Bulatov's user avatar
0 votes
1 answer
142 views

Covering number of the conditional distribution function

Suppose $Y$ is a random variable in $\mathbb{R}^d$, and we want to find the covering number \begin{equation*} \mathcal{F} = \big\{ F_{Y|W} (y | W) : y \in \mathbb{R}^d \big\} \end{equation*} where ...
香结丁's user avatar
  • 331
0 votes
0 answers
330 views

Lower-bound smallest eigenvalue of covariance matrix of $y = f(Ax)$, for $x$ uniform on unit-sphere

Let $A=(a_1,\ldots,a_)$ be a fixed $k \times d$ matrix (with $d$ large), and $x$ be a random vector uniformly distributed on the unit-sphere in $\mathbb R^d$. Let $f:\mathbb R \to \mathbb R$ be a ...
dohmatob's user avatar
  • 6,853
2 votes
1 answer
97 views

Local limit theorems for circular/spherical distributions

Here are some of the classical density functions for spherical distributions (on the $\mathcal{S}^{d-1}$ sphere, living in the Euclidean space $\mathbb{R}^d$): $$\mathbf{x}\mapsto \frac{(\kappa/2)^{d/...
Aftermath 12345's user avatar
5 votes
1 answer
150 views

Kullback–Leibler chains

The following question was asked and then deleted by the post author: Let $P$ and $Q$ be two probability distributions defined over the same space, with $KL(P \parallel Q) < \infty$. For $\epsilon ...
Iosif Pinelis's user avatar
1 vote
3 answers
269 views

Practical pseudorandom generators

It is known that existence of pseudorandom generators (PRGs) is equivalent to the existence of one-way functions. In turn, the latter is an open problem. I am curious if someone developed kind of &...
Rubi Shnol's user avatar
1 vote
0 answers
233 views

Variance-based localized Rademacher complexity for RKHS unit-ball

Let $\mathscr X$ be a compact subset of $\mathbb R^d$ (e.g the unit-sphere). Let $K: \mathscr X \times \mathscr X \to \mathbb R$ be a positive kernel function and let $\mathscr H_K$ be the induced ...
dohmatob's user avatar
  • 6,853
4 votes
2 answers
175 views

Almost independence of $x^\top a$ and $x^\top b$ for $x$ uniform on the sphere in $\mathbb R^d$ and $a,b \in \mathbb R^d$ with $a^\top b = 0$

Let $d$ be a large positive integer. Let $x$ be uniformly distributed on the unit-sphere in $\mathbb R^d$ and let $a$ and $b$ be perpendicular vectors in $\mathbb R^d$, i.e such that $a^\top b=0$. Let ...
dohmatob's user avatar
  • 6,853
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 $\...
Uzu Lim's user avatar
  • 903
1 vote
1 answer
475 views

Convergence of quadratic form $y^T Q y$ where $y$ is a random iid sequence of length $n$ and $Q$ is an $n \times n$ random matrix independent of $y$

For each positive integer, let $Q_n=(q_{i,j})_{i,j \in [n]}$ be a random $n \times n$ psd matrix. In the limit $n \to \infty$, suppose the eigenvalues of this sequence of matrices are uniformly ...
dohmatob's user avatar
  • 6,853
0 votes
1 answer
160 views

Probability to cross an envelopp for 1D random walk?

Imagine we have an evolving sequence composed of 1 and -1 (ex: -1-11-111...) where the probability to get -1 or 1 is 1/2. n is the lengh of my sequence. I can make an analogy with random walk: let ...
Jonathan's user avatar
0 votes
1 answer
100 views

Independence between $X_{n-k:n}$ and $\sum\limits_i Y_{n-i:n}-Y_{n-k:n}$

If $(X_i,Y_i), i=1,\ldots,n,$ is i.i.d sample from the joint distribution $F$ and there is dependence between the two variables say $R$. Denote the order statistics for the two variables $X_{1:n},\...
Hanan's user avatar
  • 1
1 vote
0 answers
75 views

Percentile interval Lemma

Let $\theta$ be a parameter and $\hat{\theta}$ the plug-in estimate, I need a proof of the following lemma, as given in [1], p. 173, in the form of a reference or of a direct argument: Percentile ...
Roberto Palermo's user avatar
1 vote
1 answer
135 views

KL-divergence and sub-$\sigma$-algebras

I am trying to understand if the following claim is true: Let $P$, $Q$ be probability measures on $\mathcal{X}$. For any $\sigma$-algebra $\mathcal{G}$, with countably many atoms (sets with $\...
T.T.'s user avatar
  • 13
-3 votes
1 answer
123 views

Are the first 4 statistical moments independent? [closed]

Are the first 4 statistical moments independent? Is there a mathematical demonstration that can show independence one from each other? Can the value of one moment influence the value of another? If so,...
Denis's user avatar
  • 11
2 votes
0 answers
172 views

Asymptotic lower and upper bounds for the eigenvalues of hadamard product $W \circ W$, where $W$ is a large Wishart matrix

Let $n$ and $d$ be large positive integers with $n,d \to \infty$ such that $n/d \to \gamma \in (0,\infty)$. Let $X$ be a random $n \times d$ random matrix with iid copies of log-concave isotropic ...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
769 views

sub-exponential type upper bound on the Poisson probability

I posted this question on Math Stack Exchange, though I'm not satisfied with the answer I received. Question: For a Poisson random variable $Z$ with the parameter $\lambda,\,$ what would be a good ...
Jane's user avatar
  • 11
3 votes
1 answer
194 views

On estimating Covariance between a random variable and its non-linear transform

Let $X$ be a random variable taking values on the real line. Let $R(X) = max\{0, X\}$. Is it true that the covariance $Cov[X, R(X)] \ge 0$ irrespective of the distribution of $X$? Many experiments, as ...
Trade Paul's user avatar
2 votes
2 answers
308 views

Expected value of Tukey’s half-space depth for log-concave measures

Let ${\mathbb P}$ be a probability measure in ${\mathbb R}^n$. Let $x\in{\mathbb R}^n$ be an arbitrary point. Let ${\mathbb H}_x$ be the set of halfspaces of ${\mathbb R}^n$ containing $x$. Let \begin{...
Bogdan's user avatar
  • 781
7 votes
1 answer
1k views

reverse KL-divergence: Bregman or not?

I am having a little trouble getting my head around the two "directions" of the Kullback-Leibler divergence: Definition (Kullback-Leibler divergence) For discrete probability distributions $...
jw7642's user avatar
  • 101
1 vote
1 answer
114 views

Upper bound on the ratio of Poisson CDFs [closed]

Suppose $X \sim Pois(\lambda)$. I'm interested in an upper bound on the ratio, $$\dfrac{P(X \leq n)}{P(X \leq n-1)}\,,\,\,\text{for $n=1,2,3,...$}$$ Observe that, the ratio is $>1$ & as $n \to \...
SL_MathGuy's user avatar
3 votes
2 answers
885 views

Expectation of product of random matrices

Let $X$ and $Y$ be independent random symmetric matrices. What can one say about $\mathbb{E} [X Y X Y]$ or $\mathrm{trace} \mathbb{E} [X Y X Y]$ in terms of properties of $X$ and $Y$? In particular, ...
alex's user avatar
  • 33
2 votes
1 answer
415 views

High-probability lower bound for norm of least squares solution when both design matrix $X$ and response vector $y$ are random (and independent)

Let $n,d \to \infty$ with $n/d \to \gamma \in (0,\infty)$. Let $X$ be a random $n \times d$ matrix independent rows uniformly distributed on the the unit-sphere in $\mathbb R^d$ and let $y$ be a ...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
171 views

A basic property of maximal correlation

Let $𝑋$ and $𝑌$ be random variables. Then the maximal correlation $\rho_{m}(X;Y)$ is defined as: $$\rho_{m}(X;Y):=\max_{f,g}\mathbb{E}[f(X)g(Y)],$$ where the maximization is taken over real-valued ...
Vince_maths's user avatar
1 vote
0 answers
65 views

Normalizing constants preserve metric entropy

Suppose $\mathcal{F}=\left\{f\in L^2([a,b]): 0<\underline{c}\leq f\leq\overline{c} \right\}$. Consider the following transformation $$\tilde{\mathcal{F}} := \left\{\frac{f}{\int f d\mu}: f\in \...
lucaszz's user avatar
  • 11
4 votes
1 answer
560 views

Intuition behind the noncentral chi square as Poisson mixing

It is known (cf. Wikipedia, Noncentral_chi_distribution) that the non-central chi-square distribution with k degrees of freedom is a Poisson weighted mixture of central chi-squared distributions). ...
Gabriel's user avatar
  • 43
1 vote
1 answer
144 views

Bounds for the extreme singular-values of random matrix with thresholded entries

Let $n,d,k$ be large positive integers such that $\max(n/d,k/d) =: \lambda < 1$. Let $X$ be a random $n \times d$ matrix with entries drawn iid from $N(0,1/d)$ and let $W$ be a $k \times d$ random ...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
86 views

What probability distribution is this?

Thank you in advance for any suggestions or feedback. I have a discrete 1D probability distribution represented as a vector $\textbf{p}$, $p_i = p(x_i)$. I am interested in finding the Wasserstein (...
user979797987678's user avatar
1 vote
1 answer
370 views

in Euclidean space defined by multivariate normal distribution, what fraction of points falls within n-ball (centered at origin) tangent to point p?

In a Euclidean space defined by the multivariate normal distribution, what fraction of all points falls within or are tangent to (as opposed to falling outside of) the n-sphere whose center is at the ...
aputnamist2's user avatar
2 votes
1 answer
185 views

Bayes risk of binary classification problem with conditionally independent covariates

In the setting of this problem, $\eta(\vec{x})$ is $P(Y=1|\vec{X}=\vec{x})$, $Y \in \{0,1\}$, and $X \in R^d$. Being the true probability know, the classification rule is simply $\eta(\vec{x})>0.5 \...
Data_science_apprentice's user avatar
2 votes
1 answer
118 views

Calculate the discrete probability of x number of good outcomes occurring before y number of bad outcomes

I have a grid of 16 tiles face down. Half are good outcomes and half are bad outcomes. How would I calculate the probability of picking x number of Good outcomes before y number of bad outcomes are ...
user15156281's user avatar
3 votes
0 answers
98 views

Probability measure on $\mathbb{R}^n$ with given marginals and given correlation matrix

In all what follows, let $\mathcal{P}(\mathbb{R}^n)$ denote the set of probability measures on $(\mathbb{R}^n, \mathcal{B}(\mathbb{R}^n))$ and $\mathcal{C}_n$ the set of $n \times n$ correlation ...
Tom's user avatar
  • 279
1 vote
1 answer
276 views

Upper bound for $P(X \geq x)$, where $X \sim \operatorname{Pois}(\lambda)$

I posted the following question in a comment on CDF of a log-concave discrete random variable. Since it is not related to my main question, I thought of reposting it as separate post. Question: Let $X ...
SL_MathGuy's user avatar
0 votes
1 answer
266 views

CDF of a log-concave discrete random variable

In the continuous setting, it's known that if a density function is log-concave , then its CDF is also log-concave. My questions: What can we say about this in the discrete setting?. For ex: Is the ...
SL_MathGuy's user avatar
23 votes
7 answers
5k views

What makes Gaussian distributions special?

I'm looking for as many different arguments or derivations as possible that support the informal claim that Gaussian/Normal distributions are "the most fundamental" among all distributions. ...
1 vote
1 answer
84 views

Lower bound on mean minimum distance($l_{\infty}$) between a test random vector $X'$ and vectors $X_1, \dots X_N$

Suppose we draw a independent random vector $X'$ uniformly from a unit hypercube, $[0, 1]^d$. Given similarly drawn vectors $X_1 \dots X_n$ we can define the following quantity $\rho_{\infty}(d, n):= \...
vishmay's user avatar
  • 349
2 votes
1 answer
668 views

Lower-bound for smallest eigenvalue of random $k \times $k matrix $C(W)$ defined by $C(W)_{i,j} := 2(w_i^\top w_j)^2 + \|w_i\|^2\|w_j\|^2$

Let $k$ and $d$ be positive integers such that $d/k:=\lambda > 1$. Let $W$ be $k \times d$ random matrix with rows $w_1,\ldots,w_k \in \mathbb R^d$ drawn iid from $N(0,(1/d)I_d)$, and define the $k ...
dohmatob's user avatar
  • 6,853
0 votes
2 answers
66 views

Convergence of an orthormal expansion of the density

Suppose that $X_1,..,X_n$ are i.i.d real random variables with density $f \in L_2(\mathbb R)$, and that $g_i$ are function forming an orthonormal basis of $L_2(\mathbb R)$, i.e : $$f(x) = \sum\limits_{...
lrnv's user avatar
  • 686
1 vote
0 answers
42 views

Estimation of a density by orthogonal projection

I was wandering if the following problem was already treated in the litterature. Suppose i want to estimate a density $f$ by an estimator $\hat{f}$ that i cannot explicitely describe. All i have is ...
lrnv's user avatar
  • 686
2 votes
3 answers
1k views

How can I prove Chebyshev's sum inequality with probabilistic methods?

I would like to prove Chebyshev's sum inequality, which states that: If $a_1\geq a_2\geq \cdots \geq a_n$ and $b_1\geq b_2\geq \cdots \geq b_n$, then $$ \frac{1}{n}\sum_{k=1}^n a_kb_k\geq \left(\frac{...
leevii's user avatar
  • 39
3 votes
1 answer
379 views

Concentration inequality for norm of solution to nonlinear least-squares problem

Define the piecewise-linear function $\psi(t):=\max(t,0)$ for all $t \in \mathbb R$. Let $d,n,k \to \infty$ at the same rate (i.e $n \asymp k \asymp d$). Let $y_1,\ldots,y_n \in \{-1,1\}$ uniformly ...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
68 views

(Anti-)concentration of gap between largest and second largest component of multivariate random gaussian vector

Let $n$ be a large positive integer and let $Y=(Y_1,\ldots,Y_n)$ be a zero-centered random $n$-dmensional real vector with covariance matrix $\Sigma$, an $n$-by-$n$ positive definite matrix with ...
dohmatob's user avatar
  • 6,853

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