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3 votes
1 answer
346 views

Simple anticoncentration bound for binomially distributed variable

The following question, which arose during my research, seems deceivingly simple to me, but I could not find any elegant and formal argument. For a binomially distributed variable $X \sim \text{Bin} \...
reservoir's user avatar
1 vote
0 answers
133 views

Does the Gaussian Poincare inequality hold for infinite dimensional measure metric spaces?

This is a question subsequent to the one: Does the Gaussian Poincare inequality hold for $p=1$ as well as $p=2$? There, I received a very helpful answer that the Gaussian poincare inequality for any ...
Isaac's user avatar
  • 3,477
1 vote
1 answer
227 views

Does the Gaussian Poincare inequality hold for $p=1$ as well as $p=2$?

Let $X$ be a real-valued standard normal variable. Then, for any differentiable function $f: \mathbb{R} \to \mathbb{R}$ such that $E[f(X)^2] < \infty$ and $E[\bigl( f'(X) \bigr)^2] < \infty$, it ...
Isaac's user avatar
  • 3,477
1 vote
1 answer
113 views

How to upper bound the difference between these two Gaussian-like densities?

$ \DeclareMathOperator*{\argmax}{arg\,max} \DeclareMathOperator*{\argmin}{arg\,min} \DeclareMathOperator*{\cov}{cov} \DeclareMathOperator*{\supp}{supp} \DeclareMathOperator*{\dom}{dom} \newcommand{\...
Analyst's user avatar
  • 657
1 vote
1 answer
56 views

Covariance inequality for left skewed distributions

Consider a left skewed random variable $X$ with mean $1$, median $>1$ and support on $[0,2)$. Suppose we have a class of functions $\mathbf{G}$ and each of it's members satisfy $G(x): [0,\infty) ...
Dejan Evisal's user avatar
2 votes
1 answer
335 views

The lower bound of bivariate normal distribution

Suppose $(Z_1, Z_2)$ is the zero-mean bivariate normal distribution with covariance $\left( \begin{matrix} 1 & \rho; \\ \rho & 1\end{matrix} \right)$ with positive $\rho > 0$. What I want ...
香结丁's user avatar
  • 331
1 vote
2 answers
2k views

Upper bound about Gaussian tail bound

From the definition of sub-Gaussian distribution $X$ w.r.t. $\sigma$ i.e. $$\mathbb{P}(|X-\mathbb{E}(X)|\geq t) \leq 2 \exp(-\frac{t^2}{2\sigma^2}).$$ It's natural that when $X \sim \mathcal{N}(\mu, \...
dc3506's user avatar
  • 81
0 votes
0 answers
78 views

Kernel density estimation is sub-gaussian

Let $X_1, ..., X_n$ be i.i.d. samples drawn from a pdf $f(x)$ on the real line. The kernel density estimator is defined as follows, $$\hat{f_n}(x) = \frac{1}{nh}\sum_1^n K(\frac{x-X_k}{h})$$ where $K:\...
dc3506's user avatar
  • 81
1 vote
1 answer
235 views

Prove inequality on expectation

Random variable $X\geq 0$ and its variance exists. How to prove $$\mathbb{P}(X\geq(1-t)\mathbb{E}(X))\geq \frac{t^2\mathbb{E}(X)^2}{\mathbb{E}(X^2)}\enspace\text{for}\enspace t\in(0,1]$$ $$\mathbb{E}(\...
dc3506's user avatar
  • 81
0 votes
1 answer
115 views

Approximation for an expectation expression

Let $\mathbf{x} \in \mathbb{C}^M$ is an unknown distributed random vector (certainly not gaussian), and matrix $\mathbf{A}\in \mathbb{C}^{M \times M}$ which is fix (known). Also, assume we know the ...
A. R.'s user avatar
  • 25
0 votes
1 answer
101 views

Can we show that for every $\delta>0$, there exist constants $\alpha>0, \beta>0$ so that the following inequality holds with high probability?

Consider two $n-$dimensional random vectors $u$ and $v$ uniformly distributed on the sphere. Define $X_n :=u\cdot v$. Note that as $n\to \infty$, $\sqrt{n}X_n \to N(0,1)$ as $n\to \infty$. Fix $\...
Hermi's user avatar
  • 288
7 votes
1 answer
736 views

How is the Gronwall lemma used in this paper?

Let $(X_t, t \ge 0)$ be a $\mathbb R^d$-valued stochastic process. Let $\lambda>0$. Assume we have $\mathbb E [|X_0|^2] < \infty$ and $$ \mathbb E [|X_t|^2] - \mathbb E [|X_0|^2] \le -2 \lambda \...
Akira's user avatar
  • 835
0 votes
1 answer
188 views

Equality cases in a certain case of Jensen's inequality

Suppose that $Y$ is an independent copy of a random variable (r.v.) $X$ with a zero-mean nondegenerate distribution. Is there a non-tautological, preferably simple characterization of the cases when $$...
Iosif Pinelis's user avatar
1 vote
1 answer
97 views

A strict inequality for the $L^1$-norm of a symmetrized zero-mean random variable

Suppose that $Y$ is an independent copy of a random variable (r.v.) $X$ with a zero-mean nondegenerate distribution. Is it then always true that $E|X-Y|>E|X|$? To get the non-strict version of ...
Iosif Pinelis's user avatar
3 votes
1 answer
109 views

Inequality: multivariate normal distribition

Let $p(u,x)=\frac{1}{(4\pi u)^{q/2}}e^{-|x|^2/(4u)},u>0,x \in \mathbb{R}^q.$ Prove that for $r\geq 0,c>1$ there exists $C>0$ (depending on $r,c$) such that $$\forall x \in \mathbb{R}^q,u>...
mathex's user avatar
  • 573
4 votes
1 answer
168 views

Existence of copula bound pointwise strictly smaller than the Fréchet-Hoeffding upper bound

Consider bivariate copulas $C_1$ and $C_2$ with $\max\{C_1(u,v), C_2(u,v)\}< M_2(u,v)$ for all $u,v \in(0,1)$, where $M_2(u,v) := \min\{u,v\}$ is the Fréchet-Hoeffding upper bound. Is there a ...
Corram's user avatar
  • 143
2 votes
1 answer
796 views

Can we get that $ P(N^{2/3}(\lambda_N-\lambda_{N-1})\le c)\ge 1-\epsilon$?

Following this question: Can we apply the continuous mapping theorem for the limiting joint distribution of the Tracy-Widom law?. We know that $$ \lim_{N\to\infty}P(N^{2/3}(\lambda_N-2)\le s_1,\dotsc,...
Hermi's user avatar
  • 288
0 votes
1 answer
84 views

Can we find the following $k$ so that the following inequality holds for asymptotic normal?

Following this question:Can we find such $k$ so that the following inequality holds?. Consider a sequence of independent $n-$dimensional random vectors $u, v_1, v_2,\dots, v_k$ uniformly distributed ...
Hermi's user avatar
  • 288
2 votes
3 answers
222 views

Can we find such $k$ so that the following inequality holds?

I found this question: Chernoff style concentration bound for ratio of variables. I want to ask if we get similar thing for the ratio of the sum and the one Gaussian variable. Given i.i.d. Gaussian ...
Hermi's user avatar
  • 288
2 votes
1 answer
150 views

Normalized concentration inequality for empirical CDF (iid sum)

Consider the empirical and population CDF, $$ F_n(t) = \frac{1}{n} \sum_{i=1}^n 1\{X_i \leq t\} \quad \mbox{and} \quad F(t) = \mathbb{E} [F_n(t)], $$ where above $X_1, \dots, X_n$ are iid, real-...
Drew Brady's user avatar
0 votes
0 answers
34 views

Inequalities for generalized variance

Let $(X, \mu)$ be a measured space with $\mu(X) = 1$. Given $\phi \in L^\infty(X, \mu)$, $\phi > 0$, let me define, for $\alpha \geq 1$, $\beta > 0$, the quantity $$ I(\alpha, \beta) = \left(\...
Romain Gicquaud's user avatar
0 votes
0 answers
293 views

Can we prove the following anti-concentration inequality of polynomials of square Gaussian variables?

Following this question Anti-concentration of Gaussian quadratic form. We have the following inequality: Let $X_1,\dots,X_n$ denote i.i.d. standard Gaussian random variables. For every $\epsilon>0$...
Hermi's user avatar
  • 288
4 votes
0 answers
131 views

Log of a truncated binomial

Let $X$ follow a binomial distribution with $n$ trials and success probability $p$, and let $0\leq k\leq n$. Are there any natural approximations or bounds for the ratio $$\frac{\boldsymbol{E}\log\...
Tom Solberg's user avatar
  • 4,049
1 vote
1 answer
92 views

Lower bound $L_{1}$-metric with $L_{2}$-metric for bounded pdfs, on common support

Setup To clarify, let constants $0 < a < b < \infty$, and $p \in \mathbb{N}$ be fixed. Further let $B \subset \mathbb{R}^{p}$ be a fixed compact support. We then define the space of bounded (...
user4687531's user avatar
1 vote
1 answer
362 views

An inequality involving the Wasserstein distance and chi-squared distance

$\newcommand{\N}{\mathbb N}$Let $P$ be the set of all probability mass functions on $\N_0:=\{0\}\cup\N$, where $\N:=\{1,2,\dots\}$. Let $P_{>0}$ denote the set of all $q=(q_0,q_1,\dots)\in P$ such ...
Iosif Pinelis's user avatar
7 votes
2 answers
392 views

On a von Bahr–Esseen-type inequality for pairwise independent zero-mean random variables

For $p\in(1,2)$, let $C_p$ be the smallest constant factor $C$ in the von Bahr–Esseen-type inequality \begin{equation}\label{eq:pair}\tag{1} E\Bigl\lvert\sum_{j=1}^n X_j\Bigr\rvert^p\le C\sum_{j=1}...
Iosif Pinelis's user avatar
5 votes
1 answer
288 views

Maximal inequality of iid random variables $\{X_{ij}\}_{1\leqslant i,j \leqslant n}$

Suppose that $\{X_{ij}\}_{1\leqslant i,j\leqslant n}$ are iid random variables with $\mathbb{E}(X_{11})=0$ and $\mathrm{Var}(X_{11})=1$, does the following convergence hold: $$ \max_{1\leqslant j\...
MHMH's user avatar
  • 81
1 vote
1 answer
186 views

Proof of lower bound on variance

I'm reading through the paper Poincaré type and spectral gap inequalities with fractional Laplacians on Hamming cube. However, I'm having a difficult time understanding the following proof: Lemma 2.1 ...
n3rl's user avatar
  • 13
15 votes
1 answer
703 views

Information inequalities

What are the feasible $2^n$-tuples of entropies $h(S) := H(X_{i_1},\dots,X_{i_{|S|}})$ where $X_1,\dots,X_n$ are discrete random variables with some (unknown) joint probability distribution as $S=\{...
James Propp's user avatar
  • 19.7k
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 ...
jack412's user avatar
  • 63
1 vote
1 answer
296 views

Lower bound for KL divergence of bounded densities and $L_{2}$ metric

I am currently reading "Smoothing of Multivariate Data" by Klemela. It contains Lemma 11.6, which upper and lower bounds the KL-divergence of two densities in terms of the $L_{2}$-metric. ...
user4687531's user avatar
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: $...
Mathematiger's user avatar
1 vote
0 answers
370 views

Lower bound on the sum of the product of random variables

Let $X_i$ be the $i$-th element of the vector $X=(X_1, ..., X_m)$ of i.i.d. random variables. I am looking for a lower bound for the expression $\mathbb{P}((\sum^n_{i=1}\prod^{m_i}_{j=1}(X_j))^2 \geq ...
Scriddie's user avatar
  • 129
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 ...
Enguerrand Moulinier's user avatar
1 vote
0 answers
107 views

$L^p$ inequality for "positively correlated" random variables

Suppose that we have $m$ complex-valued random variables $\xi_1,\ldots,\xi_m$ and assume the following "positive correlation" property: for all non-negative integers $\alpha_1,\ldots,\...
Alexander Kalmynin's user avatar
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/...
Trade Paul's user avatar
2 votes
0 answers
69 views

A distribution $\pi \propto \exp(-f)$ satisfies log-Sobolev inequality, does $\exp(-af)$ also satisfy LSI?

Assume a distribution $\pi \propto e^{-f}$ satisfies log-Sobolev inequality (LSI) $$\forall \rho \in P(\mathbb{R}^n), \quad KL(\rho\| \pi) \le \frac{1}{2\lambda} I(\rho \| \pi)$$ with LSI constant $\...
JIaojiao Fan's user avatar
11 votes
2 answers
934 views

Decoupling inequality/counterexample

I am embarrassed to be stuck on this seemingly simple question. Suppose that $X,Y$ are mean-zero real-valued random variables and $\tilde X,\tilde Y$ are their "independent copies": $\tilde ...
Aryeh Kontorovich's user avatar
3 votes
1 answer
142 views

How does the integral of pseudo Gaussian kernel on $(0,\infty)$ depend on its variance?

Let $a, b: \mathbb R_+ \to [0,1]$ be continuous functions. Let $k: \mathbb R_+\times\mathbb R \to [1,2]$ be $1-$Lipschitz. Set, for $0<s<t$ and $y>0$, $$A(s,t,y):=\int_s^t\frac{k(u,y)}{1+a(u)}...
user avatar
5 votes
1 answer
512 views

Concentration inequality for Hilbert space valued random variables

I have read in a paper about the following result: Let $V$ be a separable Hilbert space and $(\Omega,A_{\Omega},P)$ a probability space. Suppose that $Y_1,Y_2,...$ is a sequence of independent $V$-...
Hugo10T's user avatar
  • 115
6 votes
1 answer
1k views

Variance of the norm of a random variable under finite-moment assumptions

There is the following exercise in Vershynin's book on High-Dimensional Probability. Exercise 3.1.6: Let $X = (X_1, \dots, X_n) \in \mathbb{R}^n$ be a random vector with independent coordinates $X_i$ ...
Gautam Kamath's user avatar
4 votes
1 answer
285 views

Probability of existence of $\lambda$ such that $\lambda a_i \geq b_i$, for i.i.d random variables $a_i$'s and $b_i$'s

Suppose $a_i$'s and $b_i$'s ($1\leq i\leq n$) are i.i.d Gaussian random variables. What's the probability that a $\lambda$ exists such that $\lambda a_i \geq b_i, ~\forall i$? Actually, an upper bound ...
DSM's user avatar
  • 1,216
1 vote
1 answer
106 views

What is the maximum possible coefficient of variation for data taking values within a specified range?

I have a question that seems very basic, and yet I have not managed to find an answer after probably several hours of Google-searching. Fix $0<a<b<\infty$, and let $\mathcal{P}_{[a,b]}$ be ...
Julian Newman's user avatar
2 votes
1 answer
251 views

Log-Sobolev constant

Let $\nu \propto e^{-f}$ be a probability density on $\mathbb{R}^d$ with full support. We say $\nu$ satisfies the log-Sobolev inequality (LSI) with constant $\alpha$ if for every smooth function $g:\...
Kcafe's user avatar
  • 519
-1 votes
1 answer
551 views

Lower bound of an expectation

Suppose a random variable $X$ has unit variance i.e. $\sigma^{2} = 1$. Is there a positive constant $c > 0$ such that $$\mathbb{E}[\ | X - \mathbb{E}[X] | \ ] \ge c $$ My attempt of a solution is ...
NebulousReveal's user avatar
2 votes
2 answers
161 views

Determine the affine envelope of a random process's MGF

Suppose that a stationary random process $S(t)$ can be characterized as the figure below, which for most of the time is a straight line $S(t)=c\cdot t$, but occasionally would "stall" for a ...
leeyee's user avatar
  • 265
2 votes
1 answer
136 views

Does higher volatility of SDE imply lower probability of staying positive?

Given two SDEs $X^1$, $X^2$ : $$X^i_t=1+t+\int_0^t\sigma_i(s)dW_s,\quad \forall t\ge 0,$$ where $\sigma_i:\mathbb R_+\to [1/2,1]$ are non-decreasing s.t. $\sigma_1(t)\le \sigma_2(t)$ for all $t\ge 0$....
GJC20's user avatar
  • 1,334
2 votes
1 answer
138 views

Comparison between $\|X\|_2$ and $\|X\|_{2,1}$

For any real random variable $X$, define $$\|X\|_{2,1}=\int_0^\infty \sqrt{\Pr(|X|>t)}dt.$$ This quantity (it is not a norm) appears in various problems, e.g. the multiplier central limit theorem (...
bdx77's user avatar
  • 197
1 vote
1 answer
67 views

Lower-bound for $\mathbb E[e^{-b(v^\top X - c)^2}]$, when $X$ is log-concave in high-dimensions

Let $d$ be a large positive integer. Fix a unit-vector $v \in \mathbb R^d$, and scalars $b,c \in \mathbb R$ with $b > 0$. Let $X$ be a log-concave random vector in $\mathbb R^d$ normalized so that ...
dohmatob's user avatar
  • 6,853
0 votes
1 answer
133 views

How to demonstrate a correlation inequality? [closed]

If there are 3 vectors X, Y, Z of the same length, for any $x_i \in X,y_i \in Y,z_i \in Z$, we have $0<x_i<1,0<y_i<1,0<z_i<1$. The correlation between Z, Y is greater than between X, ...
Mac Zhang's user avatar

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