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8 votes
2 answers
5k views

Proof of Karlin-Rubin's theorem

I asked this question on Math Exchange, but as I did not receive a successful answer, maybe you could help me. Karlin-Rubin's theorem states conditions under which we can find a uniformly most ...
user39756's user avatar
  • 141
4 votes
0 answers
75 views

Marginalization of Wishart distribution

Consider the following Wishart distribution $$ f({\bf W}) = \frac{ |{\bf W}|^{(n-p-1)/2} \exp\big[-\frac{1}{2}\text{tr}({\bf V}^{-1}{\bf W} ) \big] }{2^{np/2} |{\bf V}| \Gamma_p(\frac{n}{2})} \tag{1} $...
RenatoRenatoRenato's user avatar
8 votes
3 answers
2k views

Sampling uniformly from a sphere

Let $B^{n} _p= ${$ (x_1, \dots, x_n) : |x_1|^p + \dots |x_n|^p = 1 $} be the unit ball in $\mathbb{R}^n$ in the $\ell^p$ norm. If $X_1,\dots,X_n$ are iid $\exp(1)$ -distributed random variables, then ...
Erik Aas's user avatar
  • 406
1 vote
1 answer
365 views

Lower-bound probability of non-centered quadratic form

Let $X\sim N(\mu,\sigma^2I)\in \mathbb{R}^n$ be a non-centered ($\mu\neq 0$) Gaussian vector with independent coordinates. I'm wondering if there is any sharp lower bound of the following probability: ...
neverevernever's user avatar
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
118 views

Calculate the discrete probability of x number of good outcomes occurring before y number of bad outcomes

I have a grid of 16 tiles face down. Half are good outcomes and half are bad outcomes. How would I calculate the probability of picking x number of Good outcomes before y number of bad outcomes are ...
user15156281's user avatar
1 vote
1 answer
267 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
4 votes
1 answer
561 views

Intuition behind the noncentral chi square as Poisson mixing

It is known (cf. Wikipedia, Noncentral_chi_distribution) that the non-central chi-square distribution with k degrees of freedom is a Poisson weighted mixture of central chi-squared distributions). ...
Gabriel's user avatar
  • 43
4 votes
0 answers
640 views

Comparison of concentrations of different $L^p$-norms of (sub) Gaussian distributions

It's well-known that the Euclidean $2$-norm of subgaussian random vectors concentrates in high dimensions, e.g. when $X \sim \mathcal{N}(0,I_n),$ (or in general $X$ is subgaussian with independent co-...
Learning math's user avatar
0 votes
0 answers
95 views

Empirical estimation of Brenier map from data

Let $f:\mathbb R^d \to \mathbb R$ be a "nice" (say, continuous) function define $A = A_f := \{x \in \mathbb R^d \mid f(x) \ge 0\}$ and $B =B_f:= \{x \in \mathbb R^d \mid f(x) \le 0\}$, and ...
dohmatob's user avatar
  • 6,853
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
6 votes
1 answer
1k views

Why the Fisher information matrix is equal to the Hessian matrix of the Kullback–Leibler distance at the true parameter?

I'm reading 《Algebraic geometry and statistical learning theory》.My problem is why the Fisher information matrix is equal to the Hessian matrix of the Kullback–Leibler distance at the true parameter?...
phybrain's user avatar
  • 103
1 vote
1 answer
114 views

Upper bound on the ratio of Poisson CDFs [closed]

Suppose $X \sim Pois(\lambda)$. I'm interested in an upper bound on the ratio, $$\dfrac{P(X \leq n)}{P(X \leq n-1)}\,,\,\,\text{for $n=1,2,3,...$}$$ Observe that, the ratio is $>1$ & as $n \to \...
SL_MathGuy's user avatar
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
2 answers
519 views

Cramér–Rao type bound for absolute estimation error

Let $\{X_1, X_2, \dotsc, X_n\}$ be independent and identically distributed (i.i.d.) random variables sampled from a common distribution with density $f_{\theta}(x)$, where $\theta$ is an unknown ...
Michael's user avatar
  • 544
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
0 votes
0 answers
769 views

sub-exponential type upper bound on the Poisson probability

I posted this question on Math Stack Exchange, though I'm not satisfied with the answer I received. Question: For a Poisson random variable $Z$ with the parameter $\lambda,\,$ what would be a good ...
Jane's user avatar
  • 11
1 vote
0 answers
45 views

Is there a local limit theorem for functions of Gaussian random vectors?

Assume that $\sqrt{n} (\boldsymbol{Z}_n - \boldsymbol{\mu}) \stackrel{\mathcal{D}}{\longrightarrow} \mathcal{N}(\boldsymbol{0},\Sigma)$, as $n\to \infty$, for some $\boldsymbol{\mu}\in \mathbb{R}^d$ ...
Aftermath 12345's user avatar
4 votes
5 answers
2k views

Martingales and Betting Strategies

Does anyone know of a good introduction to the theory of martingales and betting strategies from the point of view of statistics and/or probability theory? I'm looking for something basic, with lots ...
6 votes
2 answers
2k views

Interesting thesis topic on statistical inference that is sufficiently mathematical

Hello , I am a student who's gonna start honours in mathematics . Currently , I am at the stage of finding a suitable honours thesis topic . I've chosen my supervisor , who's research interest is on ...
ZOY's user avatar
  • 61
0 votes
1 answer
266 views

CDF of a log-concave discrete random variable

In the continuous setting, it's known that if a density function is log-concave , then its CDF is also log-concave. My questions: What can we say about this in the discrete setting?. For ex: Is the ...
SL_MathGuy's user avatar
1 vote
1 answer
189 views

If a Markov semigroup is eventually contractive, can we conclude that it admits a unique invariant measure?

Let $E$ be a separable $\mathbb R$-Banach space, $\rho$ be a complete separable metric on $E$, $\operatorname W_\rho$ denote the Wasserstein metric of order $1$ associated to $\rho$, $\mathcal M_1(E)$ ...
0xbadf00d's user avatar
  • 167
3 votes
0 answers
230 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
1 vote
1 answer
84 views

Lower bound on mean minimum distance($l_{\infty}$) between a test random vector $X'$ and vectors $X_1, \dots X_N$

Suppose we draw a independent random vector $X'$ uniformly from a unit hypercube, $[0, 1]^d$. Given similarly drawn vectors $X_1 \dots X_n$ we can define the following quantity $\rho_{\infty}(d, n):= \...
vishmay's user avatar
  • 349
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
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
4 votes
1 answer
344 views

Degenerate Gaussian Integral

I have an integral over a subspace of $\mathbb{R}^n \times \mathbb{R}^n$ with an integrand of the form $$\exp\left(-\frac{1}{2}\left[||u^2|| + \langle u, v \rangle + ||v||^2\right]\right)$$ The ...
DJA's user avatar
  • 435
8 votes
2 answers
980 views

Approximation of Wasserstein distance between $p_\theta$ and $p_{\theta + d\theta}$

Given a parametric family of distributions $\{p_\theta\mid\theta \in \Theta\}$, one can show that under some regularity conditions, the following approximation is valid $$\operatorname{KL}(p_\theta\...
dohmatob's user avatar
  • 6,853
1 vote
1 answer
135 views

KL-divergence and sub-$\sigma$-algebras

I am trying to understand if the following claim is true: Let $P$, $Q$ be probability measures on $\mathcal{X}$. For any $\sigma$-algebra $\mathcal{G}$, with countably many atoms (sets with $\...
T.T.'s user avatar
  • 13
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
5 votes
1 answer
429 views

Trying to understand Fisher's proof

$\newcommand{\al}{\alpha}$ For $i=1,\dots,n$, let \begin{equation} R_i:=\frac{X_i}{X_1+\dots+X_n}, \end{equation} where the $X_i$'s are iid standard exponential random variables. Let $$R_*:=\max_{1\...
Iosif Pinelis's user avatar
3 votes
2 answers
168 views

A definite integral related to sample variances of bivariate Gaussians

This integral is needed to obtain the joint distribution of the sample variances of a random sample from a bivariate Gaussian distribution. For details on the joint distribution of the sample means, ...
Chee's user avatar
  • 984
14 votes
1 answer
1k views

Berry Esseen type result for probability density functions

Let $X_1, X_2, \cdots$ be i.i.d. random variables with $E(X_1) = 0, E(X_1^2) = \sigma^2 >0, E(|X_1|^3) = \rho < \infty$. Let $Y_n = \frac{1}{n} \sum_{i=1}^n X_i$ and let us note $F_n$ (resp. $\...
Anthony Leverrier's user avatar
4 votes
3 answers
1k views

Probability theory and measuring the true strength of chessplayers

If you wanted to measure the strength of, say, a chess player, the best way would involve knowing the true value of each position: then you could compute the frequency $W$ with which the player finds ...
David Feldman's user avatar
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
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
0 votes
2 answers
66 views

Convergence of an orthormal expansion of the density

Suppose that $X_1,..,X_n$ are i.i.d real random variables with density $f \in L_2(\mathbb R)$, and that $g_i$ are function forming an orthonormal basis of $L_2(\mathbb R)$, i.e : $$f(x) = \sum\limits_{...
lrnv's user avatar
  • 686
0 votes
0 answers
86 views

What probability distribution is this?

Thank you in advance for any suggestions or feedback. I have a discrete 1D probability distribution represented as a vector $\textbf{p}$, $p_i = p(x_i)$. I am interested in finding the Wasserstein (...
user979797987678's user avatar
0 votes
1 answer
179 views

How to show $\max_{1\leq i\leq n}(X_i+Y_1)\preceq \max_{1\leq i\leq n}(X_i+Y_i)$?

Let two collections of random variables $\{X_i\}$ and $\{Y_i\}$ be independent and let $\{Y_i\}$ be i.i.d. Then $$\max_{1\leq i\leq n}(X_i+Y_1)\preceq \max_{1\leq i\leq n}(X_i+Y_i).$$ where $\...
Hermi's user avatar
  • 288
1 vote
2 answers
237 views

Fair partitioning of a set - Weighted sums of Bernoullis

For $n$ an integer, let $a_n$ be the number of ways in which one may partition the set $\{1, \ldots, 2n \}$ in two parts with: the same number of elements: $n$ and the same sum: $2n(2n+1)/4$. ...
Olivier's user avatar
  • 468
11 votes
2 answers
78k views

Coin pusher game

While doing laundry at my local laundromat, I saw a coin pusher game. Below is a picture, and here is a video depicting how it works (disregard non-coins). Essentially, one has a distribution of ...
Alex R.'s user avatar
  • 4,952
4 votes
1 answer
812 views

On the largest and smallest spacings for the uniform distribution

Let $Z_1,\dots,Z_n$ be iid random variables (r.v.'s) each uniformly distributed on $[0,1]$. Let $Z_{n:1}\le\cdots\le Z_{n:n}$ be the corresponding order statistics. For $i=1,\dots,n-1$, let $G_i:=Z_{n:...
Iosif Pinelis's user avatar
1 vote
1 answer
259 views

Test for OU-Process

Suppose that I'm given a sample from time-series $(x_n)_{n=1}^N$ and want to decide if it comes from an OU process or not. Is there a (rigorous) test I can use? So far, everything I've seen is hand-...
ABIM's user avatar
  • 5,405
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 $...
Dan Brumleve's user avatar
  • 2,302
3 votes
0 answers
98 views

Probability measure on $\mathbb{R}^n$ with given marginals and given correlation matrix

In all what follows, let $\mathcal{P}(\mathbb{R}^n)$ denote the set of probability measures on $(\mathbb{R}^n, \mathcal{B}(\mathbb{R}^n))$ and $\mathcal{C}_n$ the set of $n \times n$ correlation ...
Tom's user avatar
  • 279
0 votes
1 answer
142 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
0 votes
0 answers
331 views

Lower-bound smallest eigenvalue of covariance matrix of $y = f(Ax)$, for $x$ uniform on unit-sphere

Let $A=(a_1,\ldots,a_)$ be a fixed $k \times d$ matrix (with $d$ large), and $x$ be a random vector uniformly distributed on the unit-sphere in $\mathbb R^d$. Let $f:\mathbb R \to \mathbb R$ be a ...
dohmatob's user avatar
  • 6,853
3 votes
0 answers
307 views

Upper-bound for eigenvalues of $E [UU^T]$, where $U$ is uniformly distributed on the unit $n$-sphere

Let $X$ be a $\sigma$-subGaussian random vector on $\mathbb R^n$ (for large $n \ge 3$), meaning that the random variable $X^Tv$ is $\sigma$-subGaussian for every unit vector $v \in \mathbb R^n$. ...
dohmatob's user avatar
  • 6,853
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
1 answer
155 views

Kalman filter distribution of observation process

Let $(X_t,Y_t)$ be a pair of stochastic processes such that $$ \begin{aligned} dX_t =& A_t X_t dt + C_t dW_t,\\ dY_t = & H_t X_t dt + K_tdB_t \end{aligned} $$ for some non-random matrix-valued ...
ABIM's user avatar
  • 5,405

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