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2 votes
3 answers
183 views

Existence and sharpness of Bernstein-type bounds on the moment-generating function

Let $X$ be a centred random variable with variance $\sigma^2$, and whose moment-generating function exists in an open neighbourhood of the origin. Say that $X$ satisfies a 'Bernstein-type' MGF bound ...
πr8's user avatar
  • 801
0 votes
0 answers
57 views

Class of covariance matrices invariant under permutations

I am reading a paper on covariance matrix estimation, and in this paper is introduced a class of covariance matrices: \begin{equation} U(q, c_0(p),M)=\{\Sigma: \sigma_{ii}\leq M,\quad \max_j\sum_{j=1}^...
spenziak's user avatar
1 vote
1 answer
129 views

Small total variation distance between sums of random variables in finite Abelian group implies close to uniform?

Let $\mathbb{G} = \mathbb{Z}/p\mathbb{Z}$ (where $p$ is a prime). Let $X,Y,Z$ be independent random variables in $\mathbb G$. For a small $\epsilon$ we have $\operatorname{dist}_{TV}(X+Y,Z+Y)<\...
alon's user avatar
  • 23
0 votes
1 answer
182 views

Deducing norm concentration from MGF bounds

Suppose that $X$ is a centered, $\mathbf{R}^d$-valued random variable such that for all $t \in \mathbf{R}^d$, there holds the bound $$\log \mathbf{E} \left[ \exp \langle t, X \rangle \right] \leqslant ...
πr8's user avatar
  • 801
5 votes
1 answer
208 views

Expected supremum of normalised random walk

Let $X^i\in \mathbb R^d$ be iid. random variables for $i=1$ to $n$. Assume $\mathbb E[X^i]=0$ and the covariance matrix $\mathbb C[X^i] = \mathbb E[X^iX^{iT}] = I$ is the identity matrix. Define $S^k=...
Thomas Dybdahl Ahle's user avatar
4 votes
1 answer
358 views

Bound for type of correlation measure

Assume you have a finite, discrete probability distribution for a joint random variable and such that $P(X=i,Y=j) = p_{i,j}$ for $i \in \{1, \dots, |X|\},j \in \{1, \dots, |Y|\}$. The marginal ...
Paul's user avatar
  • 51
16 votes
3 answers
708 views

An inequality for two independent identically distributed random vectors in a normed space

Suppose that $X$ and $Y$ are independent identically distributed random vectors in a separable Banach space $B$. Does it always follow that $E\|X-Y\|\le E\|X+Y\|$? Some background information on ...
Iosif Pinelis's user avatar