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Can conditional distributions with respect to a sufficient sub-$\sigma$-algebra be represented by a single Markov kernel?

Let $(\Omega, \mathcal{F})$ be a measurable space, and let $\mathcal{P}$ be a collection of probability measures on this space. A sub-$\sigma$-algebra $\mathcal{G} \subset \mathcal{F}$ is said to be ...
MrTheOwl's user avatar
  • 111
1 vote
1 answer
56 views

How to study the convergence of the sample mode for arbitrary probability spaces

(This is not the problem I actually care about, but an analogy with similar issues to the problem I'm actually considering.) Consider a probability space with i.i.d. random variables $X_i$ producing ...
cgmil's user avatar
  • 277
0 votes
0 answers
85 views

When is a family of distributions "closed" with respect to minimal sufficient statistics?

As in the title, I am interested in understanding how to express the idea that a parametric family of distribution is "closed" with respect to minimal sufficient statistics. Before giving ...
Francesco Bilotta's user avatar
2 votes
1 answer
177 views

Optimization over Poisson-binomial distributions

I am studying the problem of how an expected utility maximizer should optimally form a portfolio of uncorrelated Bernoullis. Fix an increasing sequence of $n$ numbers in $(0,1)$, $0<p_1<\dots<...
Francesco Bilotta's user avatar
2 votes
1 answer
170 views

Law of large numbers for a continuum of Bernoullis

Suppose I have a family of $n$ independent Bernoulli random variables described by a vector of parameters $(p_i)_{i=1}^n$. As it is well known, the number of successes within this family is a random ...
Francesco Bilotta's user avatar
0 votes
0 answers
89 views

Stein's Lemma for conditional expectation?

Let $X=(X_1,\ldots,X_d)$ be a standard normal random vector in $\mathbb R^d$, let $m:\mathbb R^d \to \mathbb R$ be a function, and let $E=E_m$ denote the expectation operator conditioned on $m(X) > ...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
37 views

Compatibility of 2-copulas

An $n$-copula is the joint distribution function of a distribution on $[0,1]^n$ with uniform marginals. A family of 2-copulas $(C_{i,j})_{i<j\leq n}$ is compatible if there exists an $n$-copula $\...
Stefan Perko's user avatar
0 votes
0 answers
55 views

Modeling player interactions in multi-dimensional rating systems

In traditional rating systems (such as Elo), a player's strength is represented by a single scalar value, which is assumed to be consistent across different opponents. However, in some games, the ...
mb1's user avatar
  • 1
1 vote
0 answers
144 views

Estimator for the conditional expectation operator with convergence rate in operator norm

Let $X$ and $Z$ be two random variables defined on the same probability space, taking values in euclidian spaces $E_X$ and $E_Z$, with distributions $\pi$ and $\nu$, respectively. Let $L^2(\pi)$ ...
Caio Lins's user avatar
  • 111
0 votes
0 answers
52 views

Classifier-specific lower bounds on the misclassification rate in binary classification

Consider a binary classification problem for $(X,Y)$, and let $\hat{f}$ be a proposed classifier. We wish to bound the misclassification rate $P(\hat{f}(X)\ne Y)$. There are many known lower bounds on ...
tim523's user avatar
  • 13
0 votes
0 answers
49 views

Gaussian white noise model in application

I am interested in applications (to data) of non-parametric statistics, and my question concerned the Gaussian white noise model defined by, $$ X_{t_1, \ldots, t_d}=f\left(t_1, \ldots, t_d\right) d ...
BabaUtah's user avatar
1 vote
0 answers
68 views

Limiting value of expectation of $\operatorname{tr}(BR(z))$, where $R(z) := (X^\top X - z I_d)^{-1}$ and $X \sim N_{n,d}(0,A)$

Let $A=A(d)$, and $B=B(d)$ be (sequences of) deterministic positive-definite $d \times d$ matrices and let $X$ be an $n \times d$ random matrix with iid rows from $N(0,A)$. Let $R$ be the resolvent of ...
dohmatob's user avatar
  • 6,853
5 votes
1 answer
2k views

Mathematics research relating to machine learning

What branch/branches of math are most relevant in enhancing machine learning (mostly in terms of practical use as opposed to theoretical/possible use)? Specifically, I want to know about math research ...
Artus's user avatar
  • 173
3 votes
1 answer
257 views

Triangle equality for cosine similarity in high dimensions

I'm trying to understand whether I can use the following equality in my application -- for $u,v,w \in \mathbb{R}^d$: $$\cos(u,w)\approx \cos(u,v)\cos(v,w)$$ Where $\cos(x,y)$ gives cosine of the angle ...
Yaroslav Bulatov's user avatar
4 votes
0 answers
164 views

Convergence rates for kernel empirical risk minimization, i.e empirical risk minimization (ERM) with kernel density estimation (KDE)

Let $\Theta$ be an open subset of some $\mathbb R^m$ and let $P$ be a probability distribution on $\mathbb R^d$ with density $f$ in a Sobolev space $W_p^s(\mathbb R^d)$, i.e all derivatives of $f$ ...
dohmatob's user avatar
  • 6,853
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 ...
Steve's user avatar
  • 1,095
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
1 vote
0 answers
349 views

Tail bounds for random Gaussian chaos?

Let $g = (g_1, \dots, g_d)$ be a sequence of independent standard Normal random variables, and suppose $\Sigma$ is a $d \times d$ (deterministic), real, symmetric, positive definite matrix. The Hanson-...
Drew Brady's user avatar
3 votes
1 answer
416 views

Well-definedness of maximum likelihood estimation

Consider a family $\{\mu_\theta:\theta\in\Theta\}$ of probability measures on a measurable space $X$. Given $x\in X$, the maximum likelihood estimate is the value of $\theta$ which maximizes the ...
Quarto Bendir's user avatar
2 votes
1 answer
110 views

Lower bound on likelihood of binary outcomes

I am wondering about the following: does there exist a stochastic process $(X_n)_{n \ge 1}$ with values in $\{0,1\}$ on a probability space $(\Omega, \mathcal F, \mathbb P)$ such that for all $n \ge 1$...
Tartrate's user avatar
  • 341
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
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
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
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
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
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
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
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
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
1 answer
75 views

Density function approximation with respect to $L^1$ distance

Given iid samples $X_1,...,X_N$ drawn from some unknown distribution with not necessarily continuous density function $f(x)$ are there any theorems/papers where based on the data $X_1,...,X_N$ an ...
samb's user avatar
  • 103
0 votes
0 answers
141 views

What is the distribution of the norm of the multivariate $X \sim \mathcal{N}(\mu, \Sigma) \in \mathbb{R}^d?$

Let $X \sim \mathcal{N}(\mu, \Sigma) \in \mathbb{R}^d$ follow a multivariate normal distribution. Then what's the distribution (PDF, CDF etc.) of $X?$ When $\mu = 0, \Sigma = I_d,$ we know that $||X||...
Learning math's user avatar
1 vote
0 answers
64 views

Dependence rank: what is the size of the largest subcollection of random variables which is statistically independent?

Let $X_1,\ldots,X_p$ be random variables on the same space. Define their dependence rank, denoted $rank(X_1,\ldots,X_p)$ as the largest nonnegative integer $k$ such that there is a subcollection of $k$...
dohmatob's user avatar
  • 6,853
5 votes
1 answer
363 views

Inverse marginal property of a collection of $\sigma$-algebras

In my paper "On the inverse best approximation property of systems of subspaces of a Hilbert space" I introduced the Inverse marginal property (IMP) for a collection of $\sigma$-algebras. Let $(\...
Ivan Feshchenko's user avatar
14 votes
8 answers
3k views

Relevant mathematics to the recent coronavirus outbreak

I would like to ask about (old* and new) reliable mathematical literature relevant to various mathematical aspects of the recent coronavirus outbreak: In particular, standard statistical/mathematical ...
2 votes
1 answer
1k views

Order statistics on the spacings between order statistics for the uniform distribution

For any natural $n$, let $U_1,\dots,U_n$ be independent identically distributed random variables each uniformly distributed on the interval $[0,1]$. As usual, let $U_{n:1}\le\cdots\le U_{n:n}$ ...
Iosif Pinelis's user avatar
1 vote
1 answer
155 views

Reference request concerning order statistics from the uniform distribution

Let $U_1,\dots,U_n$ be iid random variables uniformly distributed on the interval $[0,1]$, with the corresponding order statistics $U_{(1)}\le\dots\le U_{(n)}$. Let $G_i:=U_{(i+1)}-U_{(i)}$ for $i=0,\...
Iosif Pinelis's user avatar
2 votes
1 answer
242 views

Overview of interpretations of classical probability

The Stanford Encyclopedia of Philosophy has a nice overview of numerous different interpretations of probability (classical as opposed to quantum) with an extensive bibliography. What books would ...
Tom Copeland's user avatar
  • 10.5k
2 votes
0 answers
80 views

Bridging between Rosethal Inequalities and log convex tails

Let $X_1,\ldots,X_n$ be independent with $\mathbf{E}[X_i] = 0$ and $\mathbf{E}[|X_i|^t] < \infty$ for some $t \ge 2$. Write $\|X\|_p = (E|X|^p)^{1/p}$. Then we have the classical "Rosenthal-type ...
Thomas Dybdahl Ahle's user avatar
1 vote
1 answer
41 views

Probability that maximal elements has the same position in samples from correlated random variables

Let $x$ and $y$ be two correlated random variable (say, standard normal) with correlation coefficient $\rho>0$. Let $X= \{x_1, x_2, ..., x_L\}$ and $Y= \{y_1, y_2, .. y_L\}$ be samples of size $L$ ...
mkatkov's user avatar
  • 113
2 votes
1 answer
235 views

Kolmogoroff condition for truncated random variables

Question summary. Does the Kolmogoroff condition $\sum_{n=1}^\infty\frac{\mathbb V Y_n}{n^2} < \infty$ hold for truncated random variables $Y_n := X_n \cdot 1_{\{X_n \le n\}}$ (see below for a more ...
Maximilian Janisch's user avatar
3 votes
0 answers
150 views

Central Limit Theorem for simultaneous sums

Take a sample $X_1 \ldots X_n$ of $n$ independent observations $X_j \in \mathbb{R}$ with zero mean and finite variances $\sigma_j^2$. For $i = 1, 2, \ldots$, define the sums $$S^n_i = \frac{\pm X_1 \...
user avatar
2 votes
1 answer
410 views

References for Hellinger distance/affinity involving mixture distributions

For two continuous probability distributions $F,G$ and their densities, $f,g$, the (squared) Hellinger distance/affinity is given by $d^2_H(F,G)=1-\int_{\mathbb{R}} \sqrt{fg}~dx$. Suppose that $f,g$ ...
stats134711's user avatar
3 votes
2 answers
100 views

Left tail of convex combinations of $\chi_1^2$

Suppose $a_1,...,a_n\geq0, \sum_{i=1}^na_i=1$ and $Z_1,...,Z_n$ are i.i.d. standard normal, what is a sharp upper bound of the following probability as $\delta\to0$ and what is the order? $$\mathbb{P}(...
neverevernever's user avatar
32 votes
3 answers
12k views

What is the Katz-Sarnak philosophy?

It has been recently mentioned by a speaker (his talk is completely not relevant to random matrix theory/RMT though) that modern statistics, especially random matrices theory, will help solving some ...
Henry.L's user avatar
  • 8,071
37 votes
3 answers
3k views

On Mathematical Analysis of MathSciNet & MathOverflow

This question has two original motivations: mathematical and social. The mathematical motivation is mainly based on what I have seen about Zipf's law here and there. The Zipf's law simply states ...
Morteza Azad's user avatar
3 votes
0 answers
95 views

Empirically random, quickly multiplicable matrices

I have encountered a need for fast computation of a transformation $Ax$ where $A\in \mathbb{C}^{K\times N},\ K\sim 10^7,\ N\sim 10^3$ is designed, and $x\in \mathbb{C}^N$ has iid $\mathcal{CN}(0,1)$ ...
Christian Chapman's user avatar
3 votes
1 answer
355 views

Is there a complete countable axiomatization of conditional independence? (Graphoids)

Note: A pointer to a reference, or a yes/no answer with a 1-2 sentence incomplete/non-rigorous justification would suffice for answers. I am just curious about whether the result is true; it is fairly ...
Chill2Macht's user avatar
  • 2,680
3 votes
1 answer
461 views

Bounding the "spikiness" of a probability distribution

Are there any well-known conditions that guarantee that a probability distribution isn't too "spiky"? I ask this question because I am interested in the families of probability distributions $f(x)$ ...
Tom Solberg's user avatar
  • 4,049
17 votes
4 answers
2k views

Good introduction to statistics from a algebraic point of view?

There are already lots of questions on this subject like Is there an introduction to probability theory from a structuralist/categorical perspective? Is there a combinatorial/topological treatment ...
doofin's user avatar
  • 283