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This article studies a trimmed version of the Nadaraya-Watson estimator to estimate the unknown non-parametric regression function. The characterization of the estimator through minimization problem is established, and its pointwise…

Statistics Theory · Mathematics 2019-09-27 Subhra Sankar Dhar , Prashant Jha , Prabrisha Rakhshit

In many recent studies on random walks with small jumps in the quarter plane, it has been noticed that the so-called "group" of the walk governs the behavior of a number of quantities, in particular through its "order". In this paper, when…

Probability · Mathematics 2014-07-03 Guy Fayolle , Kilian Raschel

We study some discrete symmetries of unbiased (Hadamard) and biased quantum walk on a line, which are shown to hold even when the quantum walker is subjected to environmental effects. The noise models considered in order to account for…

Quantum Physics · Physics 2009-11-13 C. M. Chandrashekar , R. Srikanth , Subhashish Banerjee

In this paper, we consider the problem of estimating the covariance kernel and its eigenvalues and eigenfunctions from sparse, irregularly observed, noise corrupted and (possibly) correlated functional data. We present a method based on…

Methodology · Statistics 2008-07-09 Debashis Paul , Jie Peng

We consider a two dimensional reflecting random walk on the nonnegative integer quadrant. This random walk is assumed to be skip free in the direction to the boundary of the quadrant, but may have unbounded jumps in the opposite direction,…

Probability · Mathematics 2014-06-24 Masahiro Kobayashi , Masakiyo Miyazawa

The deviation principles of record numbers in random walk models have not been completely investigated, especially for the non-nearest neighbor cases. In this paper, we derive the asymptotic probabilities of large and moderate deviations…

Probability · Mathematics 2022-12-07 Yuqiang Li , Qiang Yao

Quantum walks subject to decoherence generically suffer the loss of their genuine quantum feature, a quadratically faster spreading compared to classical random walks. This intuitive statement has been verified analytically for certain…

We consider random walks on discrete state spaces, such as general undirected graphs, where the random walkers are designed to approximate a target quantity over the network topology via sampling and neighborhood exploration in the form of…

Probability · Mathematics 2024-01-30 Vishwaraj Doshi , Jie Hu , Do Young Eun

We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonrandom and observation occurs in nonsynchronous manner. The problem of nonsynchronous observations is important when we consider the analysis…

Statistics Theory · Mathematics 2022-07-04 Teppei Ogihara

In this article, we consider the estimation of the structural change point in the nonparametric model with dependent observations. We introduce a maximum-CUSUM-estimation procedure, where the CUSUM statistic is constructed based on the…

Applications · Statistics 2020-12-03 Q. Yang , Y. Li , Y. Zhang

We propose and analyze a specific asymptotic stochastic order for random processes based on the measure of departure discussed in the literature. As applications, we stochastically compare mixtures of order statistics and record values…

Probability · Mathematics 2021-03-04 Sugata Ghosh , Asok K. Nanda

This paper is devoted to the parametric estimation of a shift together with the nonparametric estimation of a regression function in a semiparametric regression model. We implement a very efficient and easy to handle Robbins-Monro…

Statistics Theory · Mathematics 2012-06-05 Bernard Bercu , Philippe Fraysse

Discrete random probability measures are a key ingredient of Bayesian nonparametric inferential procedures. A sample generates ties with positive probability and a fundamental object of both theoretical and applied interest is the…

Statistics Theory · Mathematics 2021-01-20 Pierpaolo De Blasi , Ramsés H. Mena , Igor Prünster

This paper deals with a nonparametric Nadaraya-Watson estimator $\hat b$ of the drift function computed from independent continuous observations of a diffusion process. Risk bounds on $\hat b$ and its discrete-time approximation are…

Statistics Theory · Mathematics 2023-06-13 Nicolas Marie , Amélie Rosier

A parametric point process model is developed, with modeling based on the assumption that sequential observations often share latent phenomena, while also possessing idiosyncratic effects. An alternating optimization method is proposed to…

Machine Learning · Statistics 2018-02-14 Hongteng Xu , Lawrence Carin , Hongyuan Zha

The problem of detecting a few anomalous processes among a large number of data streams is considered. At each time, aggregated observations can be taken from a chosen subset of the processes, where the chosen subset conforms to a given…

Information Theory · Computer Science 2018-08-17 Chao Wang , Kobi Cohen , Qing Zhao

We study the asymptotic behaviour of additive functionals of random walks in random scenery. We establish bounds for the moments of the local time of the Kesten and Spitzer process.These bounds combined with a previous moment convergence…

Dynamical Systems · Mathematics 2021-01-05 Françoise Pene

We perform simulations for one dimensional continuous-time random walks in two dynamic random environments with fast (independent spin-flips) and slow (simple symmetric exclusion) decay of space-time correlations, respectively. We focus on…

Probability · Mathematics 2012-05-23 L. Avena , P. Thomann

We obtain exact asymptotic results for the disorder averaged persistence of a Brownian particle moving in a biased Sinai landscape. We employ a new method that maps the problem of computing the persistence to the problem of finding the…

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , Alain Comtet

The problem of detection and possible estimation of a signal generated by a dynamic system when a variable number of noisy measurements can be taken is here considered. Assuming a Markov evolution of the system (in particular, the pair…

Information Theory · Computer Science 2022-05-12 Emanuele Grossi , Marco Lops
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