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Limiting value of $\dfrac{1}{m}\mathrm{tr}(FAF^\top (FBF^\top)^{-1})$, where $F$ has iide $N(0,1)$ entries and $A,B$ are deterministic

Let $F=F_{m,d}$ be a random $m \times d$ matrix with iid entries from $N(0,1)$. Let $A=A_d$ and $B=B_d$ be deterministic $d \times d$ positive-definite matrices. In case it helps, it may be assumed ...
dohmatob's user avatar
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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 ...
PSE's user avatar
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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 ...
mzz's user avatar
  • 21
2 votes
0 answers
124 views

Rough path expected signature vs cumulant-generating function / characteristic function

What is the point of using rough path expected signature to characterize the law of а stochastic process when the cumulant generating function is known ($\log\mathbb{E}[e^{i\theta X(t)}]$)? Since an ...
anatolvitold's user avatar
2 votes
0 answers
138 views

Optimal Monte Carlo Trace Estimator

For a psd real symmetric $d\times d$ matrix $A$ and a function $f: \mathbb{R}^d \to \mathbb{R}$, with $f(x) := x^T A x$ we have that with $p(x) = \mathcal{N}(0_d, I_d)$ (i.e. standard multivariate ...
Sebastian Nowozin's user avatar
2 votes
0 answers
61 views

Approximate logarithmic bound on expected maximum via central limit theorem

If $Z_i$ are standard normal, possibly dependent, one can show that $$E\left[\max_{i=1,...,M} Z_i^2\right]\leq 3\ln M + 1.$$ I'm looking for a similar (asymptotic) bound for asymptotically normal ...
Dasherman's user avatar
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0 answers
122 views

Consistent approximation of weighted Radon transform of smooth probability density, using kernel density estimation

Let $X$ be a random vector in $\mathbb R^d$, with "sufficiently smooth" probability density function on $\rho$. For unit-vectors $w$ and $u$ in $\mathbb R^d$, and a scalar $b \in \mathbb R$, ...
dohmatob's user avatar
  • 6,853
2 votes
0 answers
87 views

The covariance of certain random variable

We define two random variables $X_n,Y_n $ on the sample space $\{1,2,3,\cdots,n\}$ with counting measure. We denote by $C_n$ the covariance of theses two random variables: $C_n=Cov(X_n,Y_n)$. ...
Ali Taghavi's user avatar
2 votes
0 answers
51 views

Spectral approximation of $(XX^\top/d)\circ(X\Sigma_dX^\top/d)$ where $X$ is an $n \times d$ random matrix with iid rows from $N(0,\Sigma_d)$

Let $X \in \mathbb R^{n \times d}$ be a random matrix with iid rows from $N(0,\Sigma_d)$ where $\Sigma_d$ is a $d \times d$ psd matrix verifying w.h.p, $\mbox{trace}(\Sigma_d/d)= 1$. $\|\Sigma_d\|_{...
dohmatob's user avatar
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2 votes
0 answers
172 views

Asymptotic lower and upper bounds for the eigenvalues of hadamard product $W \circ W$, where $W$ is a large Wishart matrix

Let $n$ and $d$ be large positive integers with $n,d \to \infty$ such that $n/d \to \gamma \in (0,\infty)$. Let $X$ be a random $n \times d$ random matrix with iid copies of log-concave isotropic ...
dohmatob's user avatar
  • 6,853
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1 answer
415 views

High-probability lower bound for norm of least squares solution when both design matrix $X$ and response vector $y$ are random (and independent)

Let $n,d \to \infty$ with $n/d \to \gamma \in (0,\infty)$. Let $X$ be a random $n \times d$ matrix independent rows uniformly distributed on the the unit-sphere in $\mathbb R^d$ and let $y$ be a ...
dohmatob's user avatar
  • 6,853
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
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
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0 answers
68 views

Approximate any point of the interval $[-1/2,1/2]$ by the sum of $n$ iid uniform random variables from $[-1,1]$

Let $x \in [-1/2,1/2]$ and $X_1,\ldots,X_n$ be drawn iid from the uniform distribution on $[-1,1]$. Question. Given $\varepsilon \ge 0$ an integer $k \in [1,n]$, what is a good lower-bound on the ...
dohmatob's user avatar
  • 6,853
2 votes
0 answers
109 views

Tightness of Hilbert-space-valued arrays

Let $\mathcal{H}$ be a separable Hilbert space. Assume we have some triangular array $W_{n,j}, j=1, \ldots ,n $ of $\mathcal{H}$-valued random elements with $\mathbb{E} \Vert W_{n,j} \Vert_{\mathcal{H}...
esner1994's user avatar
2 votes
0 answers
2k views

Approximate Multivariate Gaussian Integration by Parts

When $Z$ is a $\mathcal{N}(0,1)$ random variable, $f$ smooth from $\mathbb{R} \to \mathbb{R}$ we have the Gaussian integration by parts formula $$ \mathbb{E}(Zf(Z)) = \mathbb{E} f'(Z). $$ One analog ...
wfawwer's user avatar
  • 21
2 votes
0 answers
173 views

Weak convergence of $\mathcal{L}^2$ valued random variables

Consider two continuous functions $f,g: \mathbb{R}^{2} \rightarrow \mathbb{R}$ with $f(x,\cdot), g(x,\cdot) \in \mathcal{L}^2(\mathbb{R},\mathcal{B},\lambda)$ for all $x \in \mathbb{R}$ and a sequence ...
esner1994's user avatar
2 votes
0 answers
244 views

An inequality regarding centered Bernoulli random variables

Let $\left\{V_1,\ldots,V_n\right\}$ be a set of (possibly dependent) identically distributed Bernoulli random variables, with $$ p = \mathbb{P}\left(V_i=1\right) = 1-\mathbb{P}\left(V_i=0\right),\quad ...
Student's user avatar
  • 159
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
2 votes
0 answers
107 views

Expectation of a Random Matrix that Contains Wishart Form

I am interested in calculating the expectation of the following random matrix: $$A=WX(X^TWX)^{-1},$$ where $W \sim W_p(n,I)$ is a $p\times p$ random Wishart matrix, and $X$ is a fixed $p\times m$ ...
user482401's user avatar
2 votes
0 answers
169 views

Stochastic Approximation in Reproducing Kernel Hilbert Space

Consider an iterative algorithm with incremental updates \begin{align} x_{t+1} = x_t + \alpha_t \cdot [ h(x_t) + M_{t+1}], \end{align} where $\{x_t \}_{t \geq 0}$ is in a reproducing kernel Hilbert ...
Steve's user avatar
  • 1,127
2 votes
0 answers
46 views

increasing inter-class distances results in decreasing linear regression error

Let $\{\mathbf{x}_i, y_i \}$ be a set of binary-labeled samples ($\mathbf{x}_i \in \mathbb{R}^d, y_i \in \{a,b\}, a,b\in\mathbb{R}$). Let $\{ \mathbf{x}'_i, y_i \}$ be also such a set. Define $\mathbf{...
le4m's user avatar
  • 183
2 votes
0 answers
149 views

Min Max Equality in Information Theory

Let $\mathcal{Y}$ and $\mathcal{X}$ be finite sets and let $Q_Y$ be a fixed probability mass function on $\mathcal{Y}$. Also, let $P_{X | Y}$ be some fixed conditional distribution on $\mathcal{X} \...
R.G.'s user avatar
  • 121
2 votes
0 answers
448 views

Relation between pseudo-dimension and Rademacher complexity

With techniques of Dudley's entropy bound and Haussler's upper bound one can show that there exists a constant $C$ such that any class of $\{0,1\}$ indicator functions with Vapnik-Chervonenkis ...
axk's user avatar
  • 517
2 votes
0 answers
171 views

Distribution for the extreme values of a cumulative sum of normal variables

Suppose I have a sample $X$ of $n$ iid Normal random variables $(X_1,X_2,..,X_n)$. Now, define the sample mean $u=\frac1n\sum_{i=1}^n X_i$ and let $Y_i=X_i-u$. Let $Z_k=\sum_{i=1}^k {Y_i}$. Note ...
user1726633's user avatar
2 votes
0 answers
74 views

Best estimator for a 3 coin problem

Let $X,Y,Z$ be three unfair coins. We consider the coin $\Gamma=XI(Z=1)+YI(Z=0).$ We are given the sample $S=\{(\Gamma_i,Z_i)| i \leq n \}$ Let $k=\sum_{i \leq n}I(Z_i=1)$. For every pair of $(\...
Thomas Eberhard's user avatar
2 votes
0 answers
101 views

Best describing a stochastic process in terms of others

Intuitive Question Suppose I'm given a set of $k$ time-series $\{X_t^1,\dots X_t^k\}$. Is there a way to determine how much of each series is dependent on the others. Formal Question More ...
ABIM's user avatar
  • 5,405
2 votes
0 answers
80 views

Maximal and second max of chi-squared (normal squared) distribution

Suppose $X_i$ are i.i.d.~$\log \chi^2$ where $\chi\sim N(0,1)$ distribution, in which case $$ F(x) = \mathbb{P}\left( \log \chi^2 \le x \right) = 2\Phi(e^{x/2}) - 1, $$ and $$ f(x) = e^{x/2}\phi(e^{x/...
Nikolayevich's user avatar
2 votes
0 answers
54 views

Literature on transformed Gaussian matrices

I am considering real $n$-by-$m$ matrices of the following type: $$ M=SM^\prime,\\ M^\prime_{ij}\sim^{iid}N(0,1). $$ Here, $S$ is a fixed $n$-by-$n$ matrix and the entries of $M^\prime$ (same size ...
Vossler's user avatar
  • 121
2 votes
0 answers
87 views

A question about probabilistic graphical models

Say one is given a probabilistic graphical model and a cut of the underlying graph. Do we know any statements about when and how can one or many of the marginals (of the sources) or the conditionals (...
gradstudent's user avatar
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2 votes
0 answers
619 views

Laplace transform of a integral function of CIR/CEV process

The Cox–Ingersoll–Ross model (or CIR model) describes the evolution of interest rates. Constant elasticity of variance model (CEV) is a stochastic volatility model, which attempts to capture ...
KNN's user avatar
  • 323
2 votes
0 answers
366 views

Convergence rate of Pearson correlation matrix

I am interested in (rather sharp if not the finest) tail/concentration bounds for the Pearson correlation matrix: let $X_1,\ldots,X_N \sim \mathcal{N}(0,1)$ be correlated random variables; let $\rho(...
mic's user avatar
  • 121
2 votes
0 answers
60 views

Consistency of M-estimators when the constraint set also has to be estimated

Let $K \subset \mathbb R^n$ compact and convex. Also let $H$, $G_i, \; i \in \{1,\dotsc,m\} $: $K \to \mathbb R$ be convex functions. Assume we have the following convex optimization problem: $$ \...
air's user avatar
  • 123
2 votes
0 answers
386 views

What is the concentration of measure for Gaussian random variables which are independent, but are transformed?

This might be a too easy question for Mathoverflow, but Googling led to similar questions and answers here (though not the one I was looking for). The question is split into two: I have a matrix $X \...
kloop's user avatar
  • 131
2 votes
0 answers
175 views

Implication of MGF inequality

Let X and Y be two random variables. Denote by $F_X(x)$ and $F_Y(y)$ their CDFs and by $M_X(t)$ and $M_Y(t)$ their MGFs. It is known that X and Y have the same CDF iff they have the same MGF. My ...
axk's user avatar
  • 517
2 votes
0 answers
1k views

Converse for Levy's continuity theorem

Levy's continuity theorem states that, for a sequence of random variables $\{X_n\}$ with characteristic functions $\{\varphi_n(t)\}$ and a random variable $X$ with a characteristic function $\varphi(t)...
Bullmoose's user avatar
  • 907
2 votes
0 answers
98 views

Finding a general form of the density function when we have a four dimensional random variable

Consider a subject having time of the specific event $T_i$, which is a single sample from a distribution $F_i$ with density $f_i$ and support $[t_{\min},t_{\max}]$, for $i= 1,\ldots,n$. Let these ...
Sedi's user avatar
  • 35
2 votes
0 answers
71 views

Asymptotic results for functions of order statistics

There are $n$ ($n \ge 3$) iid random variables $\{ {c_i}\} _{i = 1}^n$ on the interval $[\underline c,\bar c]$ ($\underline c>0$). The cdf $F(\cdot)$ and pdf $f(\cdot)$ are unkown to us, but we ...
Zeta's user avatar
  • 29
2 votes
0 answers
191 views

MLRP of random variables and order statistics

Suppose we have $N$ independent random variables $X_1, \cdots, X_N$ drawn from $f_1 > \cdots > f_N$ where $f_i > f_j$ indicates that $f_i$ and $f_j$ satisfy the monotone likelihood ratio ...
user47806's user avatar
2 votes
0 answers
341 views

Marginalizing multivariate normal over defined interval

Hello everyone, I am trying to obtain an analytic expression for the following Gaussian integral $$\frac{1}{\sqrt{(2 \pi)^n |\Sigma|}} \int \kern-0.2em \cdots \kern-0.2em \int d\mathbf{x}_{\sim i} \;...
amanoel's user avatar
  • 21
2 votes
0 answers
687 views

Placing Bounds on Correlation/Covariance Through Correlation with an Intermediate Variable

I am trying to make the most of computations that have already been performed in previous steps of an algorithm. Throughout this problem statement I am only mentioning correlation, but I think it is ...
Fomalhaut's user avatar
2 votes
0 answers
265 views

Expectation of a multivariate Gaussian over a plane

For a vector $X$ which follows a multinomial Gaussian distribution $N(\vec{0},\Sigma)$, a given vector $b$, and a known scalar value $c$, I would like to calculate the expectation : $E[X|X^Tb = c]$ ...
Leo's user avatar
  • 21
2 votes
0 answers
90 views

Limiting distribution of the cardinal of a Markovian set

Let $S_1=\lbrace u_1 \rbrace$ where $u_1$ is a random uniform drawing on $[0,1]$. To build $S_{n+1}$ draw $u_{n+1}$ uniformly on $[0,1]$ (independently from previous draws) and draw $v_{n+1}$ ...
Fred jouneau sion's user avatar
2 votes
0 answers
271 views

Convergence of sample mean

I have a two-index succession of real-valued random variables $x_{t,n}$ such that $\lim_{n\to\infty} x_{t,n} = x_t$, for all $t$ and suitable limit r.v. $x_t$. I would like to prove that $$\lim_{n\to\...
Federico Poloni's user avatar
2 votes
0 answers
1k views

Random variables: multivariate second-order Taylor approximation (delta method)

Let $g:\mathbb{R}^2\rightarrow \mathbb{R}$ be a smooth, but not necessarily bounded function and $X$ and $Y$ two random variables that are not independent. (assuming they yield sufficiently many ...
madison54's user avatar
2 votes
0 answers
422 views

Generalizations of Gram-Charlier and Edgeworth series?

I am looking for references pertaining to, and/or help in deriving, generalizations of the Gram-Charlier and Edgeworth series for non-Gaussian reference probability distributions. I would like to ...
Jiahao Chen's user avatar
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2 votes
0 answers
979 views

How to calculate/approximate expectation of function of a binomial random variable?

Hi, I am stuck at following problem in my research. Suppose that $M=m$ is a random variable with binomial distribution with parameters $n,p$. The constants $r$ and $\gamma$ are greater than zero. $\...
Navneet M's user avatar
2 votes
0 answers
1k views

Moments of function of Poisson process

(I'm new to Poisson processes, so please edit if my terminology is incorrect.) Edit: per comments, here is a (more) general version of the originally posted problem (which is now at the bottom, below ...
David M Kaplan's user avatar
2 votes
0 answers
530 views

About generalization of stirling numbers of the second kind

Hello, The Stirling numbers of the second kind count how many ways can a set of $k$ elements be partitioned into $n$ non-empty classes, with $k=n,n+1,\dots$. My question is: Is there a ...
Eduardo Lopez's user avatar
2 votes
0 answers
548 views

What will be the distribution of harmonic mean of two correlated gamma random variables?

Suppose there are two correlated random variables $X_1$ and $X_2$ both are gamma distributed but having different shape and scale parameters with correlation coefficient $\rho$. What will be the ...
user8576's user avatar
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