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Related papers: Zeros of smooth stationary Gaussian processes

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In this paper we study the asymptotic theory for samples problem based on the functional empirical process (fep), this new method is called general samples problem. We suggest this method to develop the full theory of estimation of means,…

Methodology · Statistics 2025-08-12 Abdoulaye Camara , Adja Mbarka Fall , Moumouni Diallo , Gane Samb Lo

Let $(X_i)_{i\geq 1}$ be a stationary mean-zero Gaussian process with covariances $\rho(k)=\PE(X_{1}X_{k+1})$ satisfying: $\rho(0)=1$ and $\rho(k)=k^{-D} L(k)$ where $D$ is in $(0,1)$ and $L$ is slowly varying at infinity. Consider the…

Statistics Theory · Mathematics 2010-12-08 Céline Lévy-Leduc , Hélène Boistard , Eric Moulines , Murad S. Taqqu , Valderio A. Reisen

In this paper we study the asymptotic behaviour of weighted random sums when the sum process converges stably in law to a Brownian motion and the weight process has continuous trajectories, more regular than that of a Brownian motion. We…

Probability · Mathematics 2014-02-07 José Manuel Corcuera , David Nualart , Mark Podolskij

In this paper, we study the asymptotic relation between the maximum of acontinuous order statistics process formed by stationary Gaussian processesand the maximum of this process sampled at discrete time points. It is shown that, these two…

Probability · Mathematics 2019-10-18 Zhongquan Tan

The goal of this paper is to propose a new approach to asymptotic analysis of the finite predictor for stationary sequences. It produces the exact asymptotics of the relative prediction error and the partial correlation coefficients. The…

Statistics Theory · Mathematics 2025-04-03 P. Chigansky , M. Kleptsyna

This paper presents a general approach to linear stochastic processes driven by various random noises. Mathematically, such processes are described by linear stochastic differential equations of arbitrary order (the simplest non-trivial…

Condensed Matter · Physics 2009-10-28 Alon Drory

The results of a series of theoretical studies are reported, examining the convergence rate for different approximate representations of $\alpha$-stable distributions. Although they play a key role in modelling random processes with jumps…

Probability · Mathematics 2020-01-03 Marina Riabiz , Tohid Ardeshiri , Ioannis Kontoyiannis , Simon Godsill

We study the asymptotic laws for the spatial distribution and the number of connected components of zero sets of smooth Gaussian random functions of several real variables. The primary examples are various Gaussian ensembles of real-valued…

Probability · Mathematics 2016-12-21 Fedor Nazarov , Mikhail Sodin

We consider the point process of zeroes of certain Gaussian analytic functions and find the asymptotics for the probability that there are more than m points of the process in a fixed disk of radius r, as m-->infinity. For the Planar…

Probability · Mathematics 2016-09-07 Manjunath Krishnapur

Higher criticism is a large-scale testing procedure that can attain the optimal detection boundary for sparse and faint signals. However, there has been a lack of knowledge in most existing works about its asymptotic distribution for more…

Statistics Theory · Mathematics 2025-11-11 Jingkun Qiu

In the common time series model $X_{i,n} = \mu (i/n) + \varepsilon_{i,n}$ with non-stationary errors we consider the problem of detecting a significant deviation of the mean function $\mu$ from a benchmark $g (\mu )$ (such as the initial…

Statistics Theory · Mathematics 2020-05-25 Holger Dette , Florian Heinrichs

We study zeroes of Gaussian analytic functions in a strip in the complex plane, with translation-invariant distribution. We prove that the a limiting horizontal mean counting-measure of the zeroes exists almost surely, and that it is…

Probability · Mathematics 2013-07-02 Naomi Feldheim

In this paper, we study the asymptotic behavior of supremum distribution of some classes of iterated stochastic processes $\{X(Y(t)) : t \in [0, \infty)\}$, where $\{X(t) : t \in \mathbb{R} \}$ is a centered Gaussian process and $\{Y(t): t…

Probability · Mathematics 2016-04-22 Marek Arendarczyk

We construct random point processes in the complex plane that are asymptotically close to a given doubling measure. The processes we construct are the zero sets of random entire functions that are constructed through generalised Fock…

Complex Variables · Mathematics 2014-11-07 Jeremiah Buckley , Xavier Massaneda , Joaquim Ortega-Cerdà

We obtain non-asymptotic Gaussian concentration bounds for the difference between the invariant measure $\nu$ of an ergodic Brownian diffusion process and the empirical distribution of an approximating scheme with decreasing time step along…

Probability · Mathematics 2018-05-28 Igor Honoré , Stephane Menozzi , Gilles Pagès

We investigate the moments of a smooth counting function of the zeros near the central point of L-functions of weight k cuspidal newforms of prime level N. We split by the sign of the functional equations and show that for test functions…

Number Theory · Mathematics 2010-11-16 C. P. Hughes , Steven J. Miller

In this paper, we present some asymptotic properties of the normalized inverse-Gaussian process. In particular, when the concentration parameter is large, we establish an analogue of the empirical functional central limit theorem, the…

Statistics Theory · Mathematics 2012-06-29 Luai Al Labadi , Mahmoud Zarepour

For $\{X(t), t \in G_\delta\}$ a centered Gaussian process with stationary increments and a.s. sample paths on a discrete grid $G_\delta=\{0,\delta,2\delta, ...\}$, where $\delta>0$, we investigate the stationary reflected process…

Probability · Mathematics 2022-06-30 Krzysztof Dȩbicki , Grigori Jasnovidov

The paper presents a systematic theory for asymptotic inference of autocovariances of stationary processes. We consider nonparametric tests for serial correlations based on the maximum (or ${\cal L}^\infty$) and the quadratic (or ${\cal…

Statistics Theory · Mathematics 2015-03-19 Han Xiao , Wei Biao Wu

We establish that a non-Gaussian nonparametric regression model is asymptotically equivalent to a regression model with Gaussian noise. The approximation is in the sense of Le Cam's deficiency distance $\Delta $; the models are then…

Statistics Theory · Mathematics 2024-12-20 Ion Grama , Michael Nussbaum