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In this paper, we formulate and prove new properties of conditional quantiles given one of the particular sigma-fields. Next, we use them to investigate almost sure asymptotic behavior of central order statistics which arise from strictly…

Probability · Mathematics 2019-07-25 Aneta Augustynowicz

In this note, we give sufficient conditions for the almost sure and the convergence in $\mathbb{L}^p$ of a $U$-statistic of order $m$ built on a strictly stationary but not necessarily ergodic sequence.

Probability · Mathematics 2024-02-20 Davide Giraudo

In this note, we investigate the convergence of a $U$-statistic of order two having stationary ergodic data. We will find sufficient conditions for the almost sure and $L^1$ convergence and present some counter-examples showing that the…

Probability · Mathematics 2024-01-31 Herold G. Dehling , Davide Giraudo , Dalibor Volny

This paper proves several weak limit theorems for the joint version of extreme order statistics and partial sums of independently and identically distributed random variables. The results are also extended to almost sure limit version.

Probability · Mathematics 2023-12-18 Gaoyu Li , Zhongquan Tan

We study the statistics of the maximum and minimum of a set of $N$ random variables whose dynamical and statistical properties fall within the scope of infinite ergodic theory. These non-stationary yet recurrent systems are described, in…

Statistical Mechanics · Physics 2026-03-09 Talia Baravi , Eli Barkai

In this paper, we derive asymptotic results for L^1-Wasserstein distance between the distribution function and the corresponding empirical distribution function of a stationary sequence. Next, we give some applications to dynamical systems…

Probability · Mathematics 2008-12-16 Sophie Dede

This paper establishes a central limit theorem and an invariance principle for a wide class of stationary random fields under natural and easily verifiable conditions. More precisely, we deal with random fields of the form $X_k =…

Probability · Mathematics 2012-07-13 Mohamed El Machkouri , Dalibor Volny , Wei Biao Wu

A distributional symmetry is invariance of a distribution under a group of transformations. Exchangeability and stationarity are examples. We explain that a result of ergodic theory provides a law of large numbers: If the group satisfies…

Statistics Theory · Mathematics 2021-11-30 Morgane Austern , Peter Orbanz

We establish strong invariance principles for sums of stationary and ergodic processes with nearly optimal bounds. Applications to linear and some nonlinear processes are discussed. Strong laws of large numbers and laws of the iterated…

Probability · Mathematics 2011-11-10 Wei Biao Wu

We establish a connection between the structure of a stationary symmetric alpha-stable random field (0 < alpha < 2) and ergodic theory of non-singular group actions, elaborating on a previous work by Rosinski (2000). With the help of this…

Probability · Mathematics 2008-10-04 Parthanil Roy , Gennady Samorodnitsky

We study the extremes for a class of a symmetric stable random fields with long range dependence. We prove functional extremal theorems both in the space of sup measures and in the space of cadlag functions of several variables. The limits…

Probability · Mathematics 2018-10-17 Zaoli Chen , Gennady Samorodnitsky

We revisit processes generated by iterated random functions driven by a stationary and ergodic sequence. Such a process is called strongly stable if a random initialization exists, for which the process is stationary and ergodic, and for…

Probability · Mathematics 2024-02-06 László Györfi , Attila Lovas , Miklós Rásonyi

The mean ergodic theorem is equivalent to the assertion that for every function K and every epsilon, there is an n with the property that the ergodic averages A_m f are stable to within epsilon on the interval [n,K(n)]. We show that even…

Dynamical Systems · Mathematics 2016-07-15 Jeremy Avigad , Philipp Gerhardy , Henry Towsner

We establish results with an arithmetic flavor that generalize the polynomial multidimensional Szemeredi theorem and related multiple recurrence and convergence results in ergodic theory. For instance, we show that in all these statements…

Dynamical Systems · Mathematics 2015-11-19 Nikos Frantzikinakis , Bernard Host

In this note we identify the distributional limits of non-negative, ergodic stationary processes, showing that all are possible. Consequences for infinite ergodic theory are also explored and new examples of distributionally stable- and…

Dynamical Systems · Mathematics 2021-04-14 Jon. Aaronson , Benjamin Weiss

For a stationary sequence that is regularly varying and associated we give conditions which guarantee that partial sums of this sequence, under normalization related to the exponent of regular variation, converge in distribution to a…

Probability · Mathematics 2019-10-29 Adam Jakubowski

We prove limit theorems of an entirely new type for certain long memory regularly varying stationary infinitely divisible random processes. These theorems involve multiple phase transitions governed by how long the memory is. Apart from one…

Probability · Mathematics 2018-05-23 Gennady Samorodnitsky , Yizao Wang

We investigate extreme value theory of a class of random sequences defined by the all-time suprema of aggregated self-similar Gaussian processes with trend. This study is motivated by its potential applications in various areas and its…

Probability · Mathematics 2022-11-09 Lanpeng Ji , Xiaofan Peng

The first aim of the present note is to quantify the speed of convergence of a conditioned process toward its Q-process under suitable assumptions on the quasi-stationary distribution of the process. Conversely, we prove that, if a…

Probability · Mathematics 2017-04-10 Nicolas Champagnat , Denis Villemonais

We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to…

Statistical Mechanics · Physics 2015-05-13 N. R. Moloney , J. Davidsen
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