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Autoregressive models capture stochastic processes in which past realizations determine the generative distribution of new data; they arise naturally in a variety of industrial, biomedical, and financial settings. A key challenge when…

Statistics Theory · Mathematics 2020-07-30 Daren Wang , Yi Yu , Alessandro Rinaldo , Rebecca Willett

We study a minimal model for genome evolution whose elementary processes are single site mutation, duplication and deletion of sequence regions and insertion of random segments. These processes are found to generate long-range correlations…

Genomics · Quantitative Biology 2007-05-23 Philipp W. Messer , Peter F. Arndt , Michael Lässig

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of $\mathbb{R}$. An order-$1$ autoregressive model in this context is to be understood as a Markov…

Methodology · Statistics 2023-03-17 Laya Ghodrati , Victor M. Panaretos

The coding and noncoding length sequences constructed from a complete genome are characterised by multifractal analysis. The dimension spectrum $D_{q}$ and its derivative, the 'analogous' specific heat $C_{q}$, are calculated for the coding…

Biological Physics · Physics 2009-11-07 Zu-Guo Yu , Vo Anh , Ka-Sing Lau

The nature of the alignment with gaps corresponding to a longest common subsequence (LCS) of two independent iid random sequences drawn from a finite alphabet is investigated. It is shown that such an optimal alignment typically matches…

Probability · Mathematics 2016-04-22 C. Houdré , H. Matzinger

Studies of disordered heterogeneous media and galaxy cosmology share a common goal: analyzing the distribution of particles at `microscales' to predict physical properties at `macroscales', whether for a liquid, composite material, or…

Cosmology and Nongalactic Astrophysics · Physics 2023-01-11 Oliver H. E. Philcox , Salvatore Torquato

Autoregressive networks can achieve promising performance in many sequence modeling tasks with short-range dependence. However, when handling high-dimensional inputs and outputs, the huge amount of parameters in the network lead to…

Machine Learning · Computer Science 2019-09-10 Di Wang , Feiqing Huang , Jingyu Zhao , Guodong Li , Guangjian Tian

For integrated sensing and communications, an intriguing question is whether information-bearing channel-coded signals can be reused for sensing - specifically ranging. This question forces the hitherto non-overlapping fields of channel…

Signal Processing · Electrical Eng. & Systems 2025-04-01 Sundar Aditya , Morteza Varasteh , Bruno Clerckx

We develop a new methodology for the fitting of nonstationary time series that exhibit nonlinearity, asymmetry, local persistence and changes in location scale and shape of the underlying distribution. In order to achieve this goal, we…

Statistics Theory · Mathematics 2016-09-29 Alexander Aue , Rex C. Y. Cheung , Thomas C. M. Lee , Ming Zhong

In this article we review classical and recent results in anomalous diffusion and provide mechanisms useful for the study of the fundamentals of certain processes, mainly in condensed matter physics, chemistry and biology. Emphasis will be…

Statistical Mechanics · Physics 2019-02-25 Fernando A. Oliveira , Rogelma M. S. Ferreira , Luciano C. Lapas , Mendeli H. Vainstein

Time series observations are ubiquitous in astronomy, and are generated to distinguish between different types of supernovae, to detect and characterize extrasolar planets and to classify variable stars. These time series are usually…

Instrumentation and Methods for Astrophysics · Physics 2018-09-13 Susana Eyheramendy , Felipe Elorrieta , Wilfredo Palma

Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampling molecular configurations of interest can be done…

Computational Physics · Physics 2022-11-30 Kirill Shmilovich , Marc Stieffenhofer , Nicholas E. Charron , Moritz Hoffmann

A series of simulations aimed at elucidating the self-assembly dynamics of spherical virus capsids is described. This little-understood phenomenon is a fascinating example of the complex processes that occur in the simplest of organisms.…

Soft Condensed Matter · Physics 2015-05-19 D. C. Rapaport

Consider two independent random strings having same length and taking values uniformly in a common finite alphabet. We study the order of the variance of the length of the longest common subsequences (LCS) of these strings when long blocks,…

Probability · Mathematics 2016-09-26 S. Amsalu , C. Houdré , H. Matzinger

By analyzing the spacing of genes on chromosomes, we find that transcriptional and RNA-processing regulatory sequences outside coding regions leave footprints on the distribution of intergenic distances. Using analogies between genes on…

Genomics · Quantitative Biology 2008-03-11 Rutger Hermsen , Pieter Rein ten Wolde , Sarah Teichmann

Rearrangements of bacterial chromosomes can be studied mathematically at several levels, most prominently at a local, or sequence level, as well as at a topological level. The biological changes involved locally are inversions, deletions,…

Group Theory · Mathematics 2013-12-10 Andrew R. Francis

Genome sequencing is the basis for many modern biological and medicinal studies. With recent technological advances, metagenomics has become a problem of interest. This problem entails the analysis and reconstruction of multiple DNA…

Probability · Mathematics 2022-01-14 Marlee Herring

Transformers generate valid and diverse chemical structures, but little is known about the mechanisms that enable these models to capture the rules of molecular representation. We present a mechanistic analysis of autoregressive…

Machine Learning · Computer Science 2025-12-11 Kristof Varadi , Mark Marosi , Peter Antal

We investigate the Susceptible-Infectious-Recovered contagion dynamics in a system of self-propelled particles with polar alignment. Using agent-based simulations, we analyze the outbreak process for different combinations of the spatial…

Adaptation and Self-Organizing Systems · Physics 2021-06-16 Yinong Zhao , Cristián Huepe , Pawel Romanczuk

Linear autoregressive models serve as basic representations of discrete time stochastic processes. Different attempts have been made to provide non-linear versions of the basic autoregressive process, including different versions based on…

Machine Learning · Statistics 2016-03-17 Edgar A. Valencia , Mauricio A. Álvarez