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The paper deals with the problem of nonparametric estimating the $L_p$--norm, $p\in (1,\infty)$, of a probability density on $R^d$, $d\geq 1$ from independent observations. The unknown density %to be estimated is assumed to belong to a ball…

Statistics Theory · Mathematics 2020-08-26 Alexander Goldenshluger , Oleg Lepski

We propose a new method of analyzing the asymptotics of moments of certain linear random recurrences which is based on the technique of iterative functions. By using the method, we show that the moments of the number of collisions and the…

Probability · Mathematics 2011-05-11 Alexander Marynych

We study the stochastic $p$-Laplace system in a bounded domain. We propose two new space-time discretizations based on the approximation of time-averaged values. We establish linear convergence in space and $1/2$ convergence in time.…

Numerical Analysis · Mathematics 2023-05-19 Lars Diening , Martina Hofmanová , Jörn Wichmann

Fix $p\in[1,\infty)$, $K\in(0,\infty)$ and a probability measure $\mu$. We prove that for every $n\in\mathbb{N}$, $\varepsilon\in(0,1)$ and $x_1,\ldots,x_n\in L_p(\mu)$ with $\big\| \max_{i\in\{1,\ldots,n\}} |x_i| \big\|_{L_p(\mu)} \leq K$,…

Metric Geometry · Mathematics 2022-03-10 Alexandros Eskenazis

Gaussian process (GP) surrogate modeling for large computer experiments is limited by cubic runtimes, especially with data from stochastic simulations with input-dependent noise. A popular workaround to reduce computational complexity…

Methodology · Statistics 2022-06-01 D Austin Cole , Robert B Gramacy , Mike Ludkovski

Tests of fit to exact models in statistical analysis often lead to rejections even when the model is a useful approximate description of the random generator of the data. Among possible relaxations of a fixed model, the one defined by…

Optimization and Control · Mathematics 2020-09-15 Eustasio del Barrio , Hristo Inouzhe , Carlos Matrán

We establish global universal approximation theorems on spaces of piecewise linear paths, stating that linear functionals of the corresponding signatures are dense with respect to $L^p$- and weighted norms, under an integrability condition…

Probability · Mathematics 2026-03-11 Mihriban Ceylan , David J. Prömel

Convergence results for averages of independent replications of counting processes are established in a $p$-variation setting and under certain assumptions. Such convergence results can be combined with functional differentiability results…

Probability · Mathematics 2019-03-12 Morten Overgaard

We consider a linear parabolic problem with random elliptic operator in the usual Gelfand triple setting. We do not assume uniform bounds on the coercivity and boundedness constants, but allow them to be random variables. The parabolic…

Analysis of PDEs · Mathematics 2016-04-26 Stig Larsson , Christian Mollet , Matteo Molteni

This is a continuation of a project on large deviations for the empirical measures of zeros of random holomorphic sections of random line bundles over a Riemann surface X. In a previous article with O. Zeitouni (arXiv:0904.4271), we proved…

Probability · Mathematics 2013-02-05 S. Zelditch

We establish unconditional $\Omega$-results for all weighted even moments of primes in arithmetic progressions. We also study the moments of these moments and establish lower bounds under GRH. Finally, under GRH and LI we prove an…

Number Theory · Mathematics 2023-06-16 Régis de la Bretèche , Daniel Fiorilli

The Glivenko--Cantelli theorem is a uniform version of the strong law of large numbers. It states that for every IID sequence of random variables, the empirical measure converges to the underlying distribution (in the sense of uniform…

Probability · Mathematics 2026-05-13 Tobias Fritz , Tomáš Gonda , Antonio Lorenzin , Paolo Perrone , Areeb Shah Mohammed

We generalize the log Gaussian Cox process (LGCP) framework to model multiple correlated point data jointly. The observations are treated as realizations of multiple LGCPs, whose log intensities are given by linear combinations of latent…

Machine Learning · Statistics 2019-03-18 Virginia Aglietti , Theodoros Damoulas , Edwin Bonilla

Let L be a positive line bundle over a projective complex manifold X. Consider the space of holomorphic sections of the tensor power of order p of L. The determinant of a basis of this space, together with some given probability measure on…

Complex Variables · Mathematics 2016-03-14 Tien-Cuong Dinh , Viet-Anh Nguyen

We investigate the asymptotic behavior of the $L_p$-distance between a monotone function on a compact interval and a smooth estimator of this function. Our main result is a central limit theorem for the $L_p$-error of smooth isotonic…

Statistics Theory · Mathematics 2018-06-01 Hendrik P. Lopuhaä , Eni Musta

In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak--Ruppert averaged iterates generated by entropy-regularized asynchronous Q-learning with linear function approximation and a polynomial…

Machine Learning · Statistics 2026-05-19 Artemy Rubtsov , Rahul Singh , Eric Moulines , Alexey Naumov , Sergey Samsonov

Let $L$ be a linear differential operator acting on functions defined over an open set $\mathcal{D}\subset \mathbb{R}^d$. In this article, we characterize the measurable second order random fields $U = (U(x))_{x\in\mathcal{D}}$ whose sample…

Analysis of PDEs · Mathematics 2023-01-18 Iain Henderson , Pascal Noble , Olivier Roustant

Consider an intersection measure $\ell_t ^{\mathrm{IS}}$ of $p$ independent (possibly different) $m$-symmetric Hunt processes up to time $t$ in a metric measure space $E$ with a Radon measure $m$. We derive a Donsker-Varadhan type large…

Probability · Mathematics 2018-05-22 Takahiro Mori

Let $X$ be an observable random variable with unknown distribution function $F(x) = \mathbb{P}(X \leq x), - \infty < x < \infty$, and let \[\ \theta = \sup\left \{ r \geq 0:~ \mathbb{E}|X|^{r} < \infty \right \}. \] We call $\theta$ the…

Probability · Mathematics 2017-04-03 Shuhua Chang , Deli Li , Yongcheng Qi , Andrew Rosalsky

A unifying and generalizing approach to representations of the positive-part and absolute moments $\mathsf{E} X_+^p$ and $\mathsf{E}|X|^p$ of a random variable $X$ for real $p$ in terms of the characteristic function (c.f.) of $X$, as well…

Probability · Mathematics 2017-01-17 Iosif Pinelis