Skip to main content

All Questions

Filter by
Sorted by
Tagged with
2 votes
1 answer
199 views

Do enough permutations of an initial set probably cover most permutations?

Fix $\alpha, \epsilon \in(0,1)$. Take $(S_n)_n$ to be any sequence of sets with each $S_n$ containing $ \lceil (n!)^\alpha\rceil$ permutations of $n$ elements. Also build another sequence of sets $(...
Christian Chapman's user avatar
2 votes
2 answers
690 views

Concentration and anti-concentration of gap between largest and second largest value in Gaussian iid sample

Let $n \ge 3$ be an integer and let $X=(X_1,\ldots,X_n)$ be random vector with iid coordinates from $N(0,1)$. For $1 \le k \le n$, let $X_{(k)}$ be the value of the $k$th largest coordinate of $X$. ...
dohmatob's user avatar
  • 6,853
3 votes
1 answer
511 views

Complete statistical manifolds

Here, by a statistical manifold I mean a $d$-dimensional Riemannian manifold whose points are probability measures on $\mathbb{R}^n$. What are some well-studied/interesting examples of statistical ...
Catologist_who_flies_on_Monday's user avatar
6 votes
2 answers
333 views

Is there a way to reconstruct the convolution $(f * g)(x)$ of $f$ with a Gaussian $g$ from sampled values, $(f*g)(a), a \in A$?

Suppose that $f: \mathbb{R} \to \mathbb{C}$ is a function which has support in $[-1,1]$. Let $g = g_\sigma$ be a centered Gaussian with variance $\sigma^2$. Is there a way to reconstruct the ...
J. Swail's user avatar
  • 437
0 votes
1 answer
70 views

Simulation of multivariate logistic distribution conditional to a plane

For an algorithm, I have to simulate $X_1, \ldots, X_n \sim_{\text{iid}} \text{Logistic}(0,1)$ conditionally to the event $(X_1, \ldots, X_n) \in P$, where $P$ is an affine plane in $\mathbb{R}^n$. I ...
Stéphane Laurent's user avatar
7 votes
2 answers
523 views

Projections in infinite dimensional statistical manifolds

I'm struggling to understand the geometry of projection for infinite dimensional statistical manifolds. In finite dimensions, a strictly convex smooth function $F$ defines a Bregman divergence. From ...
John Rached's user avatar
1 vote
0 answers
49 views

semi-parametric regression

Suppose the observation $(X_1, Y_1), \ldots, (X_n, Y_n)$ satisfies the following semi-parametric model $$Y_t = m(X_t, \alpha) + \sigma(X_t, \beta) U_t,$$ where $U_t$ is independent with $X_t$ with ...
香结丁's user avatar
  • 331
1 vote
1 answer
261 views

Concentration inequality for a function whose parameter depends on input samples

Concentration inequalities can be used to establish results such as sample mean cannot be too far from the actual population mean, and so on. For example, let $X_1 \ldots X_n$ be i.i.d instances of a ...
Arnab's user avatar
  • 615
2 votes
2 answers
206 views

non-homogeneous counting process

Consider a counting process $\{N(t), t\geq 0\}$ where the time distribution between any two consecutive events, say $k$ and $k+1$ has a Poisson rate $\lambda(k)$, which is an explicit function of $k$....
user86217's user avatar
1 vote
0 answers
99 views

Covering number after projection

In these lecture notes on Statistical Learning Theory we find the following definitions for covering numbers: Definition. Let $(\mathcal{W}, d)$ be a metric space and $\mathcal{F} \subset \mathcal{W}$...
Jonas Metzger's user avatar
1 vote
1 answer
519 views

The integral of a Gaussian process on a unit sphere

Suppose there exist a zero-mean Gaussian process $\mathbb{G} f_u$ indexed by $u \in \mathcal{S}^{p - 1}$ with known covariance $\mathrm{E} \big[ \mathbb{G} f_u \mathbb{G} f_v \big]$ when both $u$ and $...
香结丁's user avatar
  • 331
1 vote
0 answers
910 views

Is Steven J. Miller's "research" on election fraud sound? And was he paid for it? [closed]

I recently encountered the following piece regarding alleged massive voter fraud in Pennsylvania: https://justthenews.com/sites/default/files/2020-11/...
Citizen Mathematician's user avatar
-1 votes
1 answer
2k views

how to prove that the real part and the modulus of a characteristic function is still a characterisitc function? [closed]

this is a problem from Durret's probability textbook. Show that if $\varphi$ is a ch.f., then $Re\varphi$ and $|\varphi|^2$ are also ch.f. I am wondering how to prove this. Actually I'm not even sure ...
Yilei Huang's user avatar
0 votes
1 answer
3k views

In linear regression, we have 0 training error if data dimension is high, but are there similar results for other supervised learning problems?

I tried posting this question on Cross Validated (the stack exchange for statistics) but didn't get an answer, so posting here: Let's consider a supervised learning problem where $\{(x_1,y_1) \dots (...
Learning math's user avatar
0 votes
0 answers
80 views

Can we construct a surjective mapping from $\mathbb{R}^{?}$ to this space?

(Note : I'm not sure about the tags, please re-tag this if you think you have the right tag). I am optimising a certain function over a certain space (that i will describe), and to use non-constraint ...
lrnv's user avatar
  • 686
2 votes
0 answers
140 views

Adding elements in a list *in expectation*

Suppose $𝐿_1,…,𝐿_𝑘$ are lists with $n$ elements each. We use a fully independent hash function ℎ to compute a value for each element of each list. (We suppose the hash function returns a value ...
user1246462's user avatar
1 vote
1 answer
269 views

Can I prove that a polynomial representing the 4th moment of a weighted-sum of random variables is a sos?

I am looking at the 4th central moment of a weighted-sum of correlated random variables, which takes the form $$\mu_4 = \sum_{i,j,k,l=1}^n w_i w_j w_k w_l \mu_{ijkl}$$ where $\mu_{ijkl}$ are the ...
Brian's user avatar
  • 173
4 votes
1 answer
362 views

Information monotonicity of divergence => function of $f$-divergence

It is well-known that $f$-divergences defined on $\mathcal P(\mathcal X)$ where $\mathcal X$ is a measure space with $\sigma$-algebra $\mathcal B$ satisfy the property of information monotonicity: ...
Lance's user avatar
  • 203
12 votes
4 answers
2k views

Throwing a fair die until most recent roll is smaller than previous one

I roll a fair die with $n>1$ sides until the most recent roll is smaller than the previous one. Let $E_n$ be the expected number of rolls. Do we have $\lim_{n\to\infty} E_n < \infty$? If not, ...
Dominic van der Zypen's user avatar
1 vote
0 answers
35 views

The asymptotic properties of $V$-statistic for mixing multivariate process

Suppose $\{X_t\}_{t \in \mathbb{Z}} \subseteq \mathbb{R}^d$ is a $\alpha$- or $\rho$-mixing process. Let $h (x, y) : \mathbb{R}^d \times \mathbb{R}^d \rightarrow \mathbb{R}$ be the symmetric kernel ...
香结丁's user avatar
  • 331
0 votes
1 answer
39 views

The nonparametric estimation in generalized regression model

Let $Y_t \in \mathbb{R}$ be a response variable and $X_t$ a $d$-dimensional explanatory variable. Assume we observe the process that $(X_1, Y_1), \cdots, (X_n, Y_n)$. \begin{equation} Y_{t} = \mu(...
香结丁's user avatar
  • 331
0 votes
1 answer
124 views

Question on limit in probability of the ratio of max to min of 2 sequences of non-ive, continuous iid random variables with support $[0, \infty).$

For each $ m \ge 1$, let $X_m$ and $Y_m$ be two non-negative iid random variables with the same distribution. (The distributions of $X_m$ may change with different $m$.) **Assume that their support of ...
Learning math's user avatar
2 votes
1 answer
1k views

Finding the expectation $\mathrm{E} (1/ X)$ for a negative binomial random variable $X$

Suppose a random variable $X$ is distributed as $\operatorname{NB}(\mu, \theta)$, and its mass is as follows $$ \mathrm{P}(X = y) = \binom{y + \theta - 1}{y} \left(\frac{\mu}{\mu + \theta}\right)^{y}\...
香结丁's user avatar
  • 331
0 votes
1 answer
141 views

Relaxing conditional independent assumption

Suppose we have random variables Y, D and X, where Y is independent of D conditional on X (Y⊥D|X). If there is another variable Z=f(X), where f(.) is a measurable real function, my question is: (1) ...
S.M.Hao's user avatar
  • 19
1 vote
0 answers
146 views

Bounding the probability of success of adding elements into a list

Suppose $𝐿_1,…,𝐿_𝑘$ are lists with $n$ elements each. We use a fully independent hash function ℎ to compute a value for each element of each list. (We suppose the hash function returns a value ...
user1246462's user avatar
2 votes
0 answers
49 views

What are some beginner's references on algebraically structured (statistical) models, and their connection with group actions and Fourier transform?

I asked this question on Cross Validated a few days ago, but didn't really get a favorable response, so asking here to see if I get any. I'm looking at the description of a short-term position in ...
Stat_math's user avatar
  • 223
1 vote
1 answer
266 views

Decomposition of the sum of nonnegative random variables [closed]

Non-necessarily independent random variables $X_1,~X_2,~\cdots,~X_n$ are supported on $[0,a_1],~[0,a_2],~\cdots,[0,a_n]$ and with mean values $\mu_1,~\cdots,~\mu_n$ respectively, where all $a_i$ and $\...
RyanChan's user avatar
  • 550
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 ...
aduh's user avatar
  • 869
3 votes
1 answer
902 views

Expectation of exponential of Gaussian random matrix

Let $X$ be an $(N, M)$ random Gaussian matrix where $M<N$. For a given vector $v$, I want to estimate the expectation of: \begin{align} E\left[ {{v^T}X{X^T}{v}} \right] \end{align} and \begin{align}...
hichem hb's user avatar
  • 377
1 vote
1 answer
337 views

Posterior expected value for squared Fourier coefficients of random Boolean function

Let $f : \{0, 1\}^{n} \rightarrow \{-1, 1\}$ be a Boolean function. Let the Fourier coefficients of this function be given by $$ \hat f(z) = \frac{1}{2^{n}} \sum_{x \in \{0, 1\}^{n}} f(x)(-1)^{x \cdot ...
RandomMatrices's user avatar
0 votes
1 answer
496 views

Laplace transform inversion

I have a probability distribution that is defined through it's Laplace transform by : $$L(t) = \mathbb E(e^{-tX}) = e^{1 - \frac{1+t}{t}\ln(1+t)}$$ Using R and the invLT package, i have a numerical ...
lrnv's user avatar
  • 686
3 votes
2 answers
488 views

Question about a new pseudo-random number generator

While investigating non-periodic RNG's (random number generators) for irrational numbers, I came up with a version that actually produces pseudo-random words consisting of $N$ bits, where $N$ is ...
Vincent Granville's user avatar
0 votes
1 answer
77 views

Fourth moment of a random-variable with block-tridiagonal structure

Let x be a random variable in $\mathbb{R}^d$, $J$ a block tridiagonal $d\times d$ matrix, and probability of $x$ is defined as follows $$p(x)\propto \exp(-x'Jx)$$ For a fixed $d\times d$ matrix $v$ ...
Yaroslav Bulatov's user avatar
3 votes
0 answers
229 views

Expectation of angle between two vectors in the image of a gaussian random matrix

Let $m$ and $n$ be large positive integers (going to infinity), and let $W$ be a random matrix of size $n \times m$ with iid entries from $N(0,1/m)$. Let $x,y \in \mathbb R^m$ be deterministic vectors,...
dohmatob's user avatar
  • 6,853
2 votes
2 answers
303 views

Expectation of the determinant of the inverse of non-central Wishart matrix

Let $A$ be $(n,n)$ central Wishart matrix with $k$ degrees of freedom. my question is there is a way to estimate the expectation of: \begin{align} E[det(I+(I+A)^{-1})] \end{align}
hichem hb's user avatar
  • 377
1 vote
1 answer
193 views

Compute limit of $\mathbb P(Y \le X_n)$ using limiting information on the sequence of random variables $X_n$

Let $Y$ be a symmetric random variable, $(X_n)_n$ be a sequence of nonnegative random variables, and set $p_n = \mathbb P(Y \le X_n)$. It is known from Slutsky's theorem that, if $c$ is a constant ...
dohmatob's user avatar
  • 6,853
4 votes
1 answer
156 views

When does a gaussian quadratic form converge (in probability) to a constant?

Let $(h_{ij})_{i,j \in \mathbb N}$ be a sequence of real numbers (deterministic) and let $x_1,\ldots,x_n,\ldots$ be a sequence of iid $N(0,1)$ randm variables. For each positive integer $n$, consider ...
dohmatob's user avatar
  • 6,853
1 vote
1 answer
141 views

Central limit theorem for chi-squared random field on $\mathbb R^p$

Let $X:x \mapsto X(x)$ be a centered stationary Gaussian process on the $\Omega:=\mathbb R^p$, such that $X(x) \overset{d}{=}X(x')$ for all $x,x' \in \Omega$. Set $\sigma^2 := \mbox{Var}(X(0)) = \...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
173 views

The reason why a test is undersized?

Now I have a statistic $T_n$ for testing $H_0 \leftrightarrow H_1$, and I have proved that: $$n T_n \rightarrow_d \chi_K^2$$ under $H_0$. Then an asymptotic $\chi^2$ test can be used, an asymptotic ...
香结丁's user avatar
  • 331
1 vote
0 answers
177 views

Probability of satisfying the congruent mod equation

I'm wondering about the probability of picking three different numbers $x,y,z$ out of the set $[50]=\left\{ 1,2,3,...,50\right\}$ satisfying the equation: $$xyz\equiv \gcd(x,y,z)\mod 7$$ I started out ...
Marek Kryspin's user avatar
1 vote
0 answers
46 views

How to use the mixed normal distribution to construct a proper statistics?

For a random vector $\xi_n \in \mathbb{R}^p$, if $\xi_n \rightarrow_d N(\mu, \Sigma)$, we can construct \begin{equation*} \Psi := \xi_n^{\top} \widehat{\Sigma}^{-1} \xi_n \end{equation*} for ...
香结丁's user avatar
  • 331
3 votes
0 answers
58 views

Projection onto column space perturbed by Gaussian noise

Suppose we have a matrix $X\in\mathbb{R}^{m\times n}$ (with $n \le m$) with iid standard Gaussian entries, and suppose we have noise matrix $W\in\mathbb{R}^{m\times n}$ with iid Gaussian entries, but ...
Longti's user avatar
  • 141
3 votes
1 answer
88 views

If $X \sim N(0,I_m)$, what is a necessary and sufficient condition on $u_m > 0$ such that $\lim\sup_{m\to \infty} P(\|X\|^2 \ge u_m|X_1|) = 1$

Let $m$ be a large positive integer and $X=(X_1,\ldots,X_m) \sim N(0,I_m)$. I wish to show that the squared norm of $X$ is much much bigger than the absolute value of any of the $X_j$'s. For example, ...
dohmatob's user avatar
  • 6,853
1 vote
1 answer
149 views

Asymptotics of $\chi_m$-distribution where the degree of freedom $m \to \infty?$

I'm interested to see a result where for large degree of freedom $m,$ the chi distribution $\chi_m$ is increasingly well approximated by a family of normal distributions with parameters depending on $...
Learning math's user avatar
0 votes
1 answer
428 views

First and last order statistics and their ratio for $\chi^2_{m}$ random samples

Let $X_1, \dots, X_n \sim_{iid} \chi^2_{m}$ be a random sample from a chi-squared distribution with $m$ degrees of freedom (d.f.). I was wondering if there's any known result for the order statistics $...
Learning math's user avatar
0 votes
2 answers
174 views

Asymptotic properties of ANOVA when the number of groups goes to infinity

Suppose $$X_{ij} = \mu_j + \varepsilon_{ij}, \quad j = 1, \cdots, J, \quad i = 1, \cdots, N_j$$ ANOVA can allow us to test whether $\mu_1 = \cdots = \mu_J$. In traditional ANOVA, however, the number ...
香结丁's user avatar
  • 331
1 vote
0 answers
212 views

A new notion of probability coupling

Let $X$ and $Y$ be two discrete random variables distributed according to $\mu$ and $\nu$, respectively. Consider the following optimization problems $$\inf_{\pi\in \Pi(\mu, \nu)}\Pr(X\neq Y),$$ ...
math-Student's user avatar
  • 1,109
4 votes
1 answer
320 views

The power of chi-square test

Under the null hypothesis, if we have $$\sqrt{n} \vec{x} \, \rightarrow_d \, N(0, I_p),$$ the test statistic can be construct as: $$\hat{\Psi} = n \vec{x}^{\top} \vec{x} \, \rightarrow_d \,\chi^2_p.$$ ...
香结丁's user avatar
  • 331
3 votes
0 answers
198 views

Minimizing an f-divergence and Jeffrey's Rule

My question is about f-divergences and Richard Jeffrey's (1965) rule for updating probabilities in the light of partial information. The set-up: Let $p: \mathcal{F} \rightarrow [0,1]$ be a ...
jw7642's user avatar
  • 101
1 vote
0 answers
131 views

Almost sure stochastic equicontinuity

Suppose $\mathcal{G}$ is a normed closed class of functions with finite entropy and envelope with a finite second moment (details below), and $g_0$ is a function in the interior of that class. Let $...
Caetano's user avatar
  • 59

1
5 6
7
8 9
23