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2 votes
0 answers
87 views

A complex problem involving densities (likelihood functions) and optimization

Consider the following autoregressive process with normal errors: \begin{equation}\label{7YlUV4i8nuO}\tag{I} y_t = \phi y_{t-1}+ u_t, \quad u_t \overset{iid}{\sim} N(0,\sigma^2) \end{equation} We ...
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) ...
32 votes
4 answers
7k views

Bayesian statistics for pure mathematicians

Could someone please recommend reading on Bayesian statistics presented from a pure mathematical point of view? That is, works that start assuming a good knowledge of measure theoretic probability. ...
0 votes
1 answer
327 views

Deduce that a function is zero on interval $[0,M]$

I have been thinking about this for the last few days but I was not able to produce a definitive answer. Take an integrable function $g$ that maps in $\mathbb{R}$ and with domain contained in $[0,M]$ (...
4 votes
0 answers
309 views

When is $\prod_{i=0}^\infty (I-x_i x_i^T)=0$ for zero-centered Gaussian $x_i$?

Suppose $x_i\in \mathbb{R}^d$ is sampled IID from $\mathcal{N}(0,H)$. Let $A_i=(I-x_i x_i^T)$ and assume $d$ is large. What are necessary conditions for the following to converge with probability 1? $...
1 vote
1 answer
86 views

Is the main part of certain exponential family sub-Gaussian?

$X$ is in the form of exponential family i.e. $$\mathbb{P_\theta}x = h(x)e^{\langle \theta,T(x)\rangle-\phi(\theta)}$$ where $\theta\in \mathbb{R}^d$. If $\nabla\phi(\theta)$ is L-Lipschitz i.e. $$\...
0 votes
1 answer
198 views

Spectral norm of matrices of bounded random variables

Assume $A\in \mathbb{R}^{n\times n}$ with each entry being i.i.d. bounded r.v. in $[a,b]$, is $\Vert A\Vert_2$ is sub-Gaussian? Intuitively, since $\{A_{ij}\}_{i,j=1,...,n}$ is bounded, then $$\Vert A ...
2 votes
2 answers
323 views

Continuity of Nash equilibrium for a family of games

The question may be too vague, but ultimately in search of various (counter)examples or theorems to exhibit the following: Do continuous families $t\mapsto G_t$ of "games" (say each $G_t$ is ...
2 votes
1 answer
462 views

Converse of the Herbst argument?

Background For a real-valued random variable $X$, define its entropy by $H(X) = E[\phi(X)] - \phi(E[X])$, where $\phi(u) = u \log u$. It can be shown that, if the entropy satisfies the bound $$ H(e^{\...
2 votes
1 answer
909 views

Can we use Bernstein's inequality without knowledge of variance?

I have a question about Bernstein’s inequality for bounded random variables. Its statement is the following. Let $X_1, \ldots, X_N$ be independent, mean zero random variables with $|X_i| \leq K \ (i = ...
2 votes
1 answer
415 views

Bounding Kullback-Leibler

Suppose we have a probability distribution $P$ on a finite set $S$. We draw $N$ i.i.d. samples according to $P$ and use these samples to define an empirical distribution $R$. We measure the Kullback-...
0 votes
2 answers
261 views

What mathematical formalism might be used to disprove natural selection, on the basis that there are too many independent genetic parameters? [closed]

I have nagging doubts that the random genetic mutation process of natural selection is sufficient to explain evolution, even when coupled with sexual selection (Darwin proposed that evolution is ...
4 votes
1 answer
258 views

When is $\prod_{i=0}^\infty (I-x_i x_i^T)=0$ for isotropic Gaussian $x_i$?

Suppose $x_i$ is sampled IID from isotropic zero-centered Gaussian random variable in $d$ dimensions with covariance $\Sigma=c*I$. When is the following true with probability 1? $$\prod_{i=0}^\infty (...
0 votes
1 answer
161 views

Analogues of Kac-Bernstein characterisation theorem for non-normal distributions

Let $X,Y$ be two independent random variables. The Kac-Bernstein theorem states that if $X+Y,X-Y$ are also independent, then $X,Y$ are Normal. Are there analogues of this theorem for non-normal, ...
0 votes
0 answers
60 views

Norms of Wigner matrices under power law decay

Suppose $\Sigma=\operatorname{diag}(h)$ where $h=(1^{-p},2^{-p},3^{-p},\ldots,d^{-p})$ and $p> 1$ $X$ is a matrix with $b$ rows sampled independently from $\operatorname{Normal}(0,\Sigma)$ Suppose $...
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, \...
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:\...
14 votes
1 answer
3k views

How is the "conformal prediction" conformal?

The question is clarified by Prof.V.Vovk. See his answer below for discussion. Recently, early works of Gammerman, Vanpnik and Vovk[4] are rediscovered by Wasserman et.al[1] and proposed it as a ...
1 vote
0 answers
124 views

Using projections to determine equidistribution

Suppose I have a collection of points on $\mathbb{S}^{n-1} \subset \mathbb{R}^n.$ I want to know that they are equidistributed (if you want to be more precise, you have a sequence of such collections, ...
3 votes
0 answers
93 views

Asymptotic approximation of Fisher information matrix for small Gaussian perturbation

Let $$ X=Y/a+b+\epsilon Z, $$ where $Y\sim\operatorname{Poisson}(\lambda)$ and $Z\sim\mathcal N(0,1)$ are independent. Also define $\theta=(\lambda,a,b,\epsilon)$. The Fisher information matrix $$ ...
5 votes
0 answers
1k views

Multidimensional Berry–Esseen for probability density functions

This is a follow up to this recent question: Berry Esseen type result for probability density functions There exists a multidimensional version of the usual Berry–Esseen theorem (for cumulative ...
3 votes
2 answers
505 views

Precise asymptotics for moments of order statistics of normal distribution

Let $X_1, \cdots, X_n \sim N(0,1)$ be i.i.d. normal random variates. I am interested in understanding the first two moments of the quasi-range $X_{(n)}-X_{(n-1)}$ (i.e., the maximum value minus the ...
2 votes
0 answers
62 views

Probability bounds of some ranked version of Dirichlet distribution

Recently I have come across a distribution defined on the open ranked simplex $\nabla^{n-1}_+ = \{\vec x \in \mathbb{R}^n:\sum_{k=1}^n x_k =1, x_1 \geq x_2 \geq \cdots \geq x_n > 0\}$, whose ...
9 votes
1 answer
723 views

Popular mistakes in probability

$\DeclareMathOperator\Var{Var}\DeclareMathOperator\Bern{Bern}\DeclareMathOperator\Pois{Pois}$Question: What not-trivial mistakes do students often make when solving problems in probability theory, ...
0 votes
1 answer
177 views

Under which conditions Mean Square Continuity implies Sample Continuity for Gaussian Processes?

First, let us give the setting. Let $(\Omega, \Sigma, \mathbf{P})$ be a probability space, let $T$ be some interval of time, and let $X: T \times \Omega \rightarrow S$ be a stochastic process. By Mean ...
0 votes
1 answer
218 views

Is the unconditional variance of a RV an upper bound for the variance of any conditional expectation of the RV?

Let $X$ and $Y$ be continuous random variables with finite first and second moments. Then, is it true that $Var[X]\geq Var[E(X|Y)]$?
3 votes
2 answers
247 views

Exact simulation of a large sample histogram

Say I want to create a histogram of $N$ random points from some simple compactly supported distribution on $\mathbb{R}$, where $N$ is very large, say $N = 10^{30}$. The histogram has $K$ disjoint bins,...
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 ...
1 vote
1 answer
93 views

An inequality relating $\ell_1$ distance of input and output of a Markov krnel

Let $K$ be a Markov kernel from $\mathcal{X}$ to $\mathcal{Y}$, i.e., $K(\cdot|x)$ is a probability measure on $\mathcal{Y}$ for all $x\in \mathcal{X}$. Let $\mu$ and $\nu$ be two probability measures ...
2 votes
1 answer
351 views

Lower bound on sum of independent heavy-tailed random variables

I have a sum of $n$ i.i.d random variables $X_i$ such that $E[X_i] = 0$,$\mathrm{E}[|X_i|^{1 + \delta}]$ exists for some $0 < \delta < 1$ but $\mathrm{E}[|X_i|^{1 + \delta+ \epsilon}]$ does not ...
2 votes
1 answer
122 views

Justification of the use of residual plot

$\DeclareMathOperator\Cov{Cov}$Backround of my Question Let $Y$ be the response variable, $\mathbb{X}$ be the explanatory variables. The ultimate goal of prediction is finding a function $f^{*}$ that ...
0 votes
1 answer
59 views

Given positive $\epsilon$ and $c$, find a density $\phi$ such that $t\phi(\epsilon/t) \ge c \|\phi'\|_\infty$ for all positive $t$

A nice density (on $\mathbb R$) is function $\phi:\mathbb R \to \mathbb R$ such that (1) $\phi(x) \ge 0$ for all $x \in \mathbb R$, (2) $\int_{-\infty}^\infty \phi(x) \mathrm{d}x = 1$, (3) $\phi$ is ...
6 votes
1 answer
248 views

Violating an order statistic inequality?

[Edit: for posterity, I'm adding two small comments to the code explaining how to fix it, in light of Iosef Pinelis' answer below. Look for "Should be:" to find the corrections.] Suppose we ...
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 \...
0 votes
0 answers
29 views

k-means errors for a block Gaussian vector

Consider a standard centered Gaussian vector $(X_1,...,X_n)$ with an approximate block structure, i.e. there is $q$ and a partition of $\{1,...,n\}$ in $q$ classes such that if $i,j$ are in the same ...
1 vote
0 answers
48 views

Sample complexity of estimating a doubly stochastic matrix

Let $P\in\mathbb{R}^{n\times n}$ be a doubly-stochastic matrix. That is: $$P(x,y)\geq 0,\quad \sum_xP(x,y)=1,\quad \sum_yP(x,y)=1.$$ I would like to know if lower and upper bounds on the sample ...
2 votes
2 answers
254 views

Nice way to parametrize a bunch of non-independent discrete random variables

I'm looking for a "nice" way to parametrize the joint distribution of multiple, possibly correlated discrete random variables on {0,1}. Even for N=2, there doesn't seem to be an obvious way to do it. ...
1 vote
1 answer
199 views

Rademacher complexity for a family of bounded, nondecreasing functions?

Let $\{\phi_k\}_{k=1}^K$ be a family of functions mapping from an interval $[a, b]$ to $[-1, 1]$. That is, $\phi_k \colon[ a,b] \to [-1, 1]$ are nondecreasing maps on some finite interval $[a, b] \...
3 votes
2 answers
348 views

General version of $d$-separation

I find the $d$-separation criterion (see, e.g., Theorem 2 here; note however the preceding definition, which basically means we are treating discrete random variables) a really useful sufficient ...
2 votes
1 answer
1k views

Bootstrapping and the central limit theorem

I have been looking into bootstrapping lately and although I believe to have understood the basic process somewhat, I am fuzzy on the mathematical details. I will begin with my understanding of what ...
4 votes
1 answer
626 views

How to get the lower bound of the following $\tau$?

Let $A=\{a_{ij}\}_{1\le i,j\le n}$ be an $n$ by $n$ normalized Gaussian random matrix with $E[a_{ij}]=0$ and $E[a_{ij}^2]=1/n$. Ordering its eigenvalues by $\lambda_1\le \lambda_2\le \cdots \lambda_n$ ...
15 votes
2 answers
5k views

What areas of algebra could be interesting to probability theorists?

I would like to find some topic of algebra (beyond linear algebra; algebraic number theory is fine) that would be interesting both to a student that wants to specialize in probability theory and to me ...
2 votes
2 answers
228 views

Minimal conditions on random vector $X \in R^n$ to ensure that $\lim_{t\to 0^+}\sup_{\|w\|_p = 1}\sup_{u \in \mathbb R}\mathbb P(|X'w-u| \le t)=0$

Let $X$ be a random variable on $\mathbb R^n$ and let $S_p^n := \{w \in \mathbb R^n \mid \|w\|_p = 1\}$ be the unit-sphere w.r.t to the $\ell_p$-norm in $\mathbb R^n$. We will be particularly ...
13 votes
5 answers
71k views

How do I convert a uniform value in [0,1) to a standard normal (Gaussian) distribution value?

I have uniform value in [0,1). I'd like to transform it into a standard normal distribution value, in a deterministic fashion. What I'm confused about with the Box-Muller transform is that it takes ...
1 vote
1 answer
176 views

Tight upper-bounds for the Gaussian width of intersection of intersection of hyper-ellipsoid and unit-ball

Let $\Lambda$ be a positive-definite matrix of size $n$ and let $R \ge 0$, which may depend on $n$. Consider the set $S := \{x \in \mathbb R^n \mid \|x\|_2 \le R,\,\|x\|_{\Lambda^{-1}} \le 1\}$ where $...
3 votes
1 answer
206 views

Asymptotic results for smallest gap of Gaussian random matrix

For a symmetric Gaussian random matrix $G=\{G\}_{1\le i,j \le n}$ with iid $E[G_{ij}]=0$ and $E[G_{ij}^2]=1/n$ (it is normalized), ordering its eigenvalues $\lambda_1\le \lambda_2\le\cdots \lambda_n$. ...
1 vote
0 answers
24 views

Minimax statistical estimation of proximal transform $\mbox{prox}_g(\theta_0)$, from linear model data $y_i := x_i^\top \theta_0 + \epsilon_i$

tl;dr: My question pertains the subject of minimax estimation theory (mathematical statistics), in the context of linear regression. Given a vector $\theta_0 \in \mathbb R^d$, consider the linear ...
14 votes
4 answers
2k views

How long for a simple random walk to exceed $\sqrt{T}$?

Let $R_n$ be a simple random walk with $R_0 = 0$, and let $T$ be the smallest index such that $k\sqrt{T} < |R_T|$ for some positive $k$. What is an expression for the probability distribution of $...
3 votes
1 answer
549 views

Does $E[1/f]\overset{d}\to 1/E[f]$ for $\operatorname{Tr}H=1,\operatorname{Tr}H^2=0.5$?

Suppose $x$ is a Gaussian random variable in $d$ dimensions with $H=E[xx^T],\ \operatorname{Tr}(H)=1,\operatorname{Tr}(H^2)=0.5$. Take $m$ I.I.D. samples of $x$ and stack them as rows of $X$. Is it ...
2 votes
1 answer
304 views

An approximation problem w.r.t marginal distribution of coordinates of uniform random vector on high-dimensional unit-sphere

Let $X=(X_1,\ldots,X_d)$ be uniformly distributed on the sphere of radius $\sqrt{d}$ in $\mathbb R^d$. Fix a "sufficiently integrable" function $h:\mathbb R \to \mathbb R$, and define ...

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