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We study the nonequilibrium steady state realized in a general stochastic system attached to multiple heat baths and/or driven by an external force. Starting from the detailed fluctuation theorem we derive concise and suggestive expressions…

Statistical Mechanics · Physics 2009-11-13 Teruhisa S. Komatsu , Naoko Nakagawa

Let $\{X(\mathbf{t}):\mathbf{t}=(t_1, t_2, \ldots, t_d)\in[0,\infty)^d\}$ be a centered stationary Gaussian field with almost surely continuous sample paths, unit variance and correlation function $r$ satisfying conditions $r(\mathbf{t})<1$…

Probability · Mathematics 2018-05-14 Natalia Soja-Kukieła

The recent contribution Dieker & Mikosch (2015) [1] obtained important representations of max-stable stationary Brown-Resnick random fields $\zeta_Z$ with a spectral representation determined by a Gaussian process $Z$. With motivations from…

Probability · Mathematics 2017-06-13 Enkelejd Hashorva

Consider a first-order autoregressive process $X_i=\beta X_{i-1}+\varepsilon_i,$ where $\varepsilon_i=G(\eta_i,\eta_{i-1},\ldots)$ and $\eta_i,i\in\mathbb{Z}$ are i.i.d. random variables. Motivated by two important issues for the inference…

Statistics Theory · Mathematics 2013-12-12 Ngai Hang Chan , Rongmao Zhang

Skew-symmetric families of distributions such as the skew-normal and skew-$t$ represent supersets of the normal and $t$ distributions, and they exhibit richer classes of extremal behaviour. By defining a non-stationary skew-normal process,…

Methodology · Statistics 2016-04-19 Boris Beranger , Simone A. Padoan , Scott A. Sisson

Let $\{\zeta_{m,k}^{(\kappa)}(t), t \ge0\}, \kappa>0$ be random processes defined as the differences of two independent stationary chi-type processes with $m$ and $k$ degrees of freedom. In applications such as physical sciences and…

Probability · Mathematics 2016-07-18 P. Albin , E. Hashorva , L. Ji , C. Ling

For the stationary storage process $\{Q(t), t\ge0\}$, with $ Q(t)=\sup_{ s \ge t}\left(X(s)-X(t)-c(s-t)^\beta\right), $ where $\{X(t),t\ge 0\}$ is a centered Gaussian process with stationary increments, $c>0$ and $\beta>0$ is chosen such…

Probability · Mathematics 2015-06-22 Krzysztof Dȩbicki , Peng Liu

A stochastically continuous process $\xi(t)$, $t\geq0$, is said to be time-stable if the sum of $n$ i.i.d. copies of $\xi$ equals in distribution to the time-scaled stochastic process $\xi(nt)$, $t\geq0$. The paper advances the…

Probability · Mathematics 2015-04-14 Christoph Kopp , Ilya Molchanov

In recent years, parametric models for max-stable processes have become a popular choice for modeling spatial extremes because they arise as the asymptotic limit of rescaled maxima of independent and identically distributed random…

Methodology · Statistics 2025-05-14 Carolin Forster , Marco Oesting

We propose the entropy of random Markov trajectories originating and terminating at a state as a measure of the stability of a state of a Markov process. These entropies can be computed in terms of the entropy rates and stationary…

Dynamical Systems · Mathematics 2020-02-11 Marc Harper , Dashiell Fryer

We consider a one-dimensional stationary time series of fixed duration $T$. We investigate the time $t_{\rm m}$ at which the process reaches the global maximum within the time interval $[0,T]$. By using a path-decomposition technique, we…

Statistical Mechanics · Physics 2022-11-23 Francesco Mori , Satya N. Majumdar , Gregory Schehr

The notion of stability can be generalised to point processes by defining the scaling operation in a randomised way: scaling a configuration by $t$ corresponds to letting such a configuration evolve according to a Markov branching particle…

Probability · Mathematics 2015-10-28 Giacomo Zanella , Sergei Zuyev

For stationary sequences, under general local and asymptotic dependence restrictions, any limiting point process for time normalized upcrossings of high levels is a compound Poisson process, i.e., there is a clustering of high upcrossings,…

Statistics Theory · Mathematics 2012-04-10 João Renato Sebastião , Ana Paula Martins , Helena Ferreira , Luísa Pereira

In this paper, we prove that the kappa distribution is the stationary solution of the Vlasov-Poisson system in an inhomogeneous plasma under the polytropic equation of state and an assumption restricting the local velocity distribution to a…

Plasma Physics · Physics 2020-12-17 Ran Guo

This work defines and investigates the properties of the Max-U-Exp distribution. The method of moments is applied in order to estimate its parameters. Then, by using the previous general theory about Mixed Poisson processes, developed by…

Probability · Mathematics 2024-02-15 Pavlina K. Jordanova , Evelina Veleva

We introduce a functional domain of attraction approach for stochastic processes, which is more general than the usual one based on weak convergence. The distribution function G of a continuous max-stable process on [0,1] is introduced and…

Probability · Mathematics 2012-11-13 Stefan Aulbach , Michael Falk , Martin Hofmann

We call a point process $Z$ on $\mathbb R$ \emph{exp-1-stable} if for every $\alpha,\beta\in\mathbb R$ with $e^\alpha+e^\beta=1$, $Z$ is equal in law to $T_\alpha Z+T_\beta Z'$, where $Z'$ is an independent copy of $Z$ and $T_x$ is the…

Probability · Mathematics 2013-01-22 Pascal Maillard

In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between global stationarity and nonstationarity for both parametric…

Statistics Theory · Mathematics 2020-05-04 Sucharita Roy , Sourabh Bhattacharya

Aulbach et al. (2013) introduced a max-domain of attraction approach for extreme value theory in C[0,1] based on functional distribution functions, which is more general than the approach based on weak convergence in de Haan and Lin (2001).…

Probability · Mathematics 2014-12-12 Stefan Aulbach , Michael Falk , Martin Hofmann , Maximilian Zott

We consider the random field M(t)=\sup_{n\geq 1}\big\{-\log A_{n}+X_{n}(t)\big\}\,,\qquad t\in T\, for a set $T\subset \mathbb{R}^{m}$, where $(X_{n})$ is an iid sequence of centered Gaussian random fields on $T$ and $0<A_{1}<A_{2}<\cdots $…

Probability · Mathematics 2018-03-28 Zhipeng Liu , Jose H. Blanchet , A. B. Dieker , Thomas Mikosch