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The telegraph process $\{X(t), t>0\}$, is supposed to be observed at $n+1$ equidistant time points $t_i=i\Delta_n,i=0,1,..., n$. The unknown value of $\lambda$, the underlying rate of the Poisson process, is a parameter to be estimated. The…

Probability · Mathematics 2007-06-13 stefano m. iacus , nakahiro yoshida

We investigate the effects of the resetting mechanism to the origin for a random motion on the real line characterized by two alternating velocities $v_1$ and $v_2$. We assume that the sequences of random times concerning the motions along…

Probability · Mathematics 2023-10-17 Antonio Di Crescenzo , Antonella Iuliano , Verdiana Mustaro , Gabriella Verasani

We consider a problem of estimation for the telegrapher's process on the line, say X(t), driven by a Poisson process with non constant rate. It turns out that the finite-dimensional law of the process X(t) is a solution to the telegraph…

Probability · Mathematics 2007-06-13 Stefano M. Iacus

We are interested in estimating the location of what we call "smooth change-point" from $n$ independent observations of an inhomogeneous Poisson process. The smooth change-point is a transition of the intensity function of the process from…

Statistics Theory · Mathematics 2021-02-17 A. Amiri , S Dachian

In this paper we consider a telegraph equation with time-dependent coefficients, governing the persistent random walk of a particle moving on the line with a time-varying velocity $c(t)$ and changing direction at instants distributed…

Probability · Mathematics 2020-01-09 Luca Angelani , Roberto Garra

Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the…

Instrumentation and Methods for Astrophysics · Physics 2021-03-24 Cong Xu , Hans Moritz Günther , Vinay L. Kashyap , Thomas C. M. Lee , Andreas Zezas

The telegraph process $X(t)$, $t>0$, (Goldstein, 1951) and the geometric telegraph process $S(t) = s_0 \exp\{(\mu -\frac12\sigma^2)t + \sigma X(t)\}$ with $\mu$ a known constant and $\sigma>0$ a parameter are supposed to be observed at…

Statistics Theory · Mathematics 2007-06-13 Alessandro De Gregorio , Stefano M. Iacus

The aim of change-point detection is to identify behavioral shifts within time series data. This article focuses on scenarios where the data is derived from an inhomogeneous Poisson process or a marked Poisson process. We present a…

Methodology · Statistics 2024-11-07 C. Dion-Blanc , D. Hawat , E. Lebarbier , S. Robin

We study online change point detection for multivariate inhomogeneous Poisson point process time series. This setting arises commonly in applications such as earthquake seismology, climate monitoring, and epidemic surveillance, yet remains…

We consider the telegraph process with two velocities, $a_1>a_2\in\mathbb{R}$, and two rates of reversal, $\lambda_1,\lambda_2>0$. We study some of its features with respect to the conditional probability measure where both the initial…

Probability · Mathematics 2022-02-07 Fabrizio Cinque

We treat the change point problem in ergodic diffusion processes from discrete observations. Tonaki et al. (2020) proposed adaptive tests for detecting changes in the diffusion and drift parameters in ergodic diffusion models. When any…

Statistics Theory · Mathematics 2021-02-16 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

A validated simulation model primarily requires performing an appropriate input analysis mainly by determining the behavior of real-world processes using probability distributions. In many practical cases, probability distributions of the…

Applications · Statistics 2014-09-01 Issac Shams , Saeede Ajorlou , Kai Yang

The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on non-parametric divergence estimation…

Machine Learning · Statistics 2015-03-20 Song Liu , Makoto Yamada , Nigel Collier , Masashi Sugiyama

We consider a random trial-based telegraph process, which describes a motion on the real line with two constant velocities along opposite directions. At each epoch of the underlying counting process the new velocity is determined by the…

Probability · Mathematics 2013-12-17 Irene Crimaldi , Antonio Di Crescenzo , Antonella Iuliano , Barbara Martinucci

We analyze the one-dimensional telegraph random process confined by two boundaries, 0 and $H>0$. The process experiences hard reflection at the boundaries (with random switching to full absorption). Namely, when the process hits the origin…

Probability · Mathematics 2020-03-16 Antonio Di Crescenzo , Barbara Martinucci , Paola Paraggio , Shelemyahu Zacks

Random motions on the line and on the plane with space-varying velocities are considered and analyzed in this paper. On the line we investigate symmetric and asymmetric telegraph processes with space-dependent velocities and we are able to…

Probability · Mathematics 2016-09-16 R. Garra , E. Orsingher

We present a detection problem where several spatially distributed sensors observe Poisson signals emitted from a single source of unknown position. The measurements at each sensor are modeled by independent inhomogeneous Poisson processes.…

Statistics Theory · Mathematics 2018-06-19 Christian Farinetto , Yury A. Kutoyants , Alioune Top

We consider the problem of locating a jump discontinuity (change-point) in a smooth parametric regression model with a bounded covariate. It is assumed that one can sample the covariate at different values and measure the corresponding…

Statistics Theory · Mathematics 2009-08-14 Yan Lan , Moulinath Banerjee , George Michailidis

Turbulent relative dispersion is studied theoretically with a focus on the evolution of probability distribution of the relative separation of two passive particles. A finite separation speed and a finite correlation of relative velocity,…

Chaotic Dynamics · Physics 2007-05-23 Takeshi Ogasawara , Sadayoshi Toh

In this work we consider time series with a finite number of discrete point changes. We assume that the data in each segment follows a different probability density functions (pdf). We focus on the case where the data in all segments are…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ali Mohammad-Djafari , Olivier Feron
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