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Record statistics is the study of how new highs or lows are created and sustained in any dynamical process. The study of the highest or lowest records constitute the study of extreme values. This paper represents an exploration of record…

Statistical Mechanics · Physics 2015-03-27 Shashi C. L. Srivastava , Arul Lakshminarayan

In this article two methods to distinguish between polynomial and exponential tails are introduced. The methods are mainly based on the properties of the residual coefficient of variation for the exponential and non-exponential…

Methodology · Statistics 2011-12-21 Joan del Castillo , Jalila Daoudi , Richard Lockhart

We provide a method that enables the simple calculation of the maximal correlation coefficient of a bivariate distribution, under suitable conditions. In particular, the method readily applies to known results on order statistics and…

Methodology · Statistics 2016-11-18 Nickos Papadatos , Tatiana Xifara

We present a new, scalable alternative to the structured singular value, which we call $\nu$, provide a convex upper bound, study their properties and compare them to $\ell_1$ robust control. The analysis relies on a novel result on the…

Optimization and Control · Mathematics 2022-04-13 Olle Kjellqvist , John C. Doyle

We study the restricted growth function associated with set partitions, and obtain exact formulas for the number of strong records with height one, the total of record heights over set of partitions, and the number of partitions with a…

Combinatorics · Mathematics 2019-08-05 Toufik Mansour , Reza Rastegar , Alexander Roitershtein

For measuring tail risk with scarce extreme events, extreme value analysis is often invoked as the statistical tool to extrapolate to the tail of a distribution. The presence of large datasets benefits tail risk analysis by providing more…

Methodology · Statistics 2023-12-18 Liujun Chen , Deyuan Li , Chen Zhou

Consider a finite set of sources, each producing i.i.d. observations that follow a unique probability distribution on a finite alphabet. We study the problem of matching a finite set of observed sequences to the set of sources under the…

Information Theory · Computer Science 2014-12-09 Jayakrishnan Unnikrishnan

We evaluate analytically and numerically the size of the frozen core and various scaling laws for critical Boolean networks that have a power-law in- and/or out-degree distribution. To this purpose, we generalize an efficient method that…

Molecular Networks · Quantitative Biology 2015-06-12 Marco Möller , Barbara Drossel

For a sequence $\{X_{n}, \, n \geqslant 1 \}$ of random variables satisfying $\mathbb{E} \lvert X_{n} \rvert < \infty$ for all $n \geqslant 1$, a maximal inequality is established, and used to obtain strong law of large numbers for…

Probability · Mathematics 2022-12-26 João Lita da Silva

We study the distribution $P(x;\alpha,L)$ of the relative trend $x$ in long-term correlated records of length $L$ that are characterized by a Hurst-exponent $\alpha$ between 0.5 and 1.5 obtained by DFA2. The relative trend $x$ is the ratio…

Data Analysis, Statistics and Probability · Physics 2015-06-23 Araik Tamazian , Josef Ludescher , Armin Bunde

We investigate the predictability problem in dynamical systems with many degrees of freedom and a wide spectrum of temporal scales. In particular, we study the case of $3D$ turbulence at high Reynolds numbers by introducing a finite-size…

chao-dyn · Physics 2009-10-28 E. Aurell , G. Boffetta , A. Crisanti , G. Paladin , A. Vulpiani

By constructing jointly a random graph and an associated exploration process, we define the dynamics of a "parking process" on a class of uniform random graphs as a measure-valued Markov process, representing the empirical degree…

Probability · Mathematics 2015-04-14 Paola Bermolen , Matthieu Jonckheere , Pascal Moyal

On a variety of tasks, the performance of neural networks predictably improves with training time, dataset size and model size across many orders of magnitude. This phenomenon is known as a neural scaling law. Of fundamental importance is…

Machine Learning · Statistics 2024-06-25 Blake Bordelon , Alexander Atanasov , Cengiz Pehlevan

A pattern of a sequence is a sequence of integer indices with each index describing the order of first occurrence of the respective symbol in the original sequence. In a recent paper, tight general bounds on the block entropy of patterns of…

Information Theory · Computer Science 2007-11-15 Gil I. Shamir

In this work, we deal with extreme value theory in the context of continued fractions using techniques from probability theory, ergodic theory and real analysis. We give an upper bound for the rate of convergence in the Doeblin-Iosifescu…

Probability · Mathematics 2019-08-06 Anish Ghosh , Maxim Kirsebom , Parthanil Roy

We study the asymptotic number of certain monotonically labeled increasing trees arising from a generalized evolution process. The main difference between the presented model and the classical model of binary increasing trees is that the…

Combinatorics · Mathematics 2019-10-30 Olivier Bodini , Antoine Genitrini , Bernhard Gittenberger , Stephan Wagner

We explore how the asymptotic structure of a random $n$-term weak integer composition of $m$ evolves, as $m$ increases from zero. The primary focus is on establishing thresholds for the appearance and disappearance of substructures. These…

Combinatorics · Mathematics 2024-12-20 David Bevan , Dan Threlfall

A famous result by Hammersley and Versik-Kerov states that the length $L_n$ of the longest increasing subsequence among $n$ iid continuous random variables grows like $2\sqrt{n}$. We investigate here the asymptotic behavior of $L_n$ for…

Combinatorics · Mathematics 2025-11-24 Anne-Laure Basdevant , Lucas Gerin , Maxime Marivain

We report further findings on the size distribution of the largest neutral segments in a sequence of N randomly charged monomers [D. Ertas and Y. Kantor, Phys. Rev. E53, 846 (1996); cond-mat/9507005]. Upon mapping to one--dimensional random…

Condensed Matter · Physics 2009-10-28 Deniz Ertas , Yacov Kantor

We introduce a generalized homogeneous function to describe the joint probability density for magnitude and duration of events in self-organized critical systems (SOC). It follows that the cumulative distributions of magnitude and of…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 J. Feder , H. Nordhagen , W. A. Watters