# Questions tagged [pr.probability]

Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory.

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### expectation of the function of Wishart matrix eigenvalues

For Given a $N×M$ random complex gaussian matrix $X$ where $M=XX^H$, let $\lambda_1>\lambda_2>....>\lambda_N$ be the ordered eigenvalues of $M$ my objective is to get an estimation of \begin{...
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### Intuition behind Gubinelli derivative

I apologise for the confusion of the following sentences. I'm lazy to give more information about Rough path theory as Is a fairly broad subject. On page 14 of "A Course on Rough Paths With an ...
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### How to understand the distance between two edges on a graph in the bond percolation? [closed]

onsider the Euclidean lattice $\mathbb{Z}^d$ and the graph $G=(V(\mathbb{Z}^d), E(\mathbb{Z}^d))$, I try to define $\{f:d(e,f)>k\}$ for a constant $k$ where $e, f$ are two edges in $E(\mathbb{Z}^d)$...
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### 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-...
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### How to solve this stochastic optimization problem?

How one can solve the following stochastic optimization problem? \begin{align} \max\quad& \mathbb{E}[\mathbf{1}^{\mathrm{T}}X]\\ \text{s.t.} \quad& \mathbb{E}[\mathbf{A}X]\leq\mathbf{1}_{m\...
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### 2-d geometric Brownian motion hitting time distribution

I am trying to solve following problem: Given two independent geometric Brownian motions $\frac{d x_t}{x_t}=\mu_x dt + \sigma_x dw_t^x$ and $\frac{d y_t}{y_t}=\mu_y dt + \sigma_y dW_t^y$ and ...
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### Sampling i.i.d. variables with restrictions

General Problem: Suppose $X_1,\ldots,X_n \sim \mathbb{P}_X^{\otimes n}$ is a finite sequence of i.i.d. (real- or integer-valued) random variables. Suppose $A\subseteq \mathbb{R}^n$ is a set of "...
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### Probability that a Voronoi cell contains exactly k random points

Consider two independent point processes in the unit square $[0,1]^2$. The two point processes are identically independent and typically binomial/Poisson. One, say $\Phi^*$, is used to generate a ...