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We study effects of strategy-dependent time delays on equilibria of evolving populations. It is well known that time delays may cause oscillations in dynamical systems. Here we report a novel behavior. We show that microscopic models of…

Populations and Evolution · Quantitative Biology 2021-04-13 Jacek Miȩkisz , Marek Bodnar

We show how machine learning methods can unveil the fractional and delayed nature of discrete dynamical systems. In particular, we study the case of the fractional delayed logistic map. We show that given a trajectory, we can detect if it…

Dynamical Systems · Mathematics 2023-09-08 J. Alberto Conejero , Òscar Garibo-i-Orts , Carlos Lizama

Generalist predators consist an important component of an ecosystem which may act as a biocontrol agent and influence the dynamics significantly. In this paper, we have studied the effect of delayed logistic growth of the prey species with…

Dynamical Systems · Mathematics 2022-02-16 Rajesh Ranjan Patra , Soumen Kundu , Sarit Maitra

Generative modeling of spatio-temporal fields is crucial for a variety of applications, including stochastic weather generators and climate-model surrogates. However, many such fields exhibit complex dependence structures that vary across…

Methodology · Statistics 2026-05-06 Carrie J. Lei-Cramer , Jian Cao , Matthias Katzfuss

We derive an alternative expression for a delayed logistic equation in which the rate of change in the population involves a growth rate that depends on the population density during an earlier time period. In our formulation, the delay in…

Dynamical Systems · Mathematics 2022-06-07 Chiu-Ju Lin , Ting-Hao Hsu , Gail S. K. Wolkowicz

We aim to explicitly model the delayed Granger causal effects based on multivariate Hawkes processes. The idea is inspired by the fact that a causal event usually takes some time to exert an effect. Studying this time lag itself is of…

Machine Learning · Computer Science 2023-08-14 Chao Yang , Hengyuan Miao , Shuang Li

We propose here a method to estimate a delay from a time series taking advantage of analysis of random walks with delay. This method is applicable to a time series coming out of a system which is or can be approximated as a linear feedback…

Statistical Mechanics · Physics 2009-10-30 Toru Ohira , Ryusuke Sawatari

Our study focuses on analyzing the behavior of a stochastic predator-prey model with a time delay and logistic growth of prey, influenced by L\'{e}vy noise. Initially, we establish the existence, uniqueness, and boundedness of a positive…

Dynamical Systems · Mathematics 2023-04-26 Jaouad Danane , Delfim F. M. Torres

We consider the effects of temporal delay in a neural feedback system with excitation and inhibition. The topology of our model system reflects the anatomy of the avian isthmic circuitry, a feedback structure found in all classes of…

Biological Physics · Physics 2007-09-18 Sebastian F. Brandt , Ralf Wessel

Traditionally, Hawkes processes are used to model time--continuous point processes with history dependence. Here we propose an extended model where the self--effects are of both excitatory and inhibitory type and follow a Gaussian Process.…

Machine Learning · Statistics 2021-05-21 Noa Malem-Shinitski , Cesar Ojeda , Manfred Opper

In this paper, we investigate the global boundedness, asymptotic stability and pattern formation of predator-prey systems with density-dependent preytaxis in a two-dimensional bounded domain with Neumann boundary conditions, where the…

Analysis of PDEs · Mathematics 2019-07-05 Hai-Yang Jin , Zhi-An Wang

Time delay is ubiquitous in many experimental and real-world situations. It is often unclear whether time delay plays a significant role in observed phenomena, and if it does, how long the time lag really is. This would be invaluable…

Data Analysis, Statistics and Probability · Physics 2025-12-10 Robin A. Kopp , Sabine H. L. Klapp , Deepak Gupta

Due to their flexibility, Gaussian processes (GPs) have been widely used in nonparametric function estimation. A prior information about the underlying function is often available. For instance, the physical system (computer model output)…

Methodology · Statistics 2017-11-21 Hassan Maatouk

We study the effects of noise on the dynamics of a system of coupled self-propelling particles in the case where the coupling is time-delayed, and the delays are discrete and randomly generated. Previous work has demonstrated that the…

Pattern Formation and Solitons · Physics 2012-10-08 Brandon Lindley , Luis Mier-y-Teran-Romero , Ira B. Schwartz

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which a linear path functional of the…

Probability · Mathematics 2013-10-17 Salvatore Federico , Peter Tankov

The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in various contexts. Here we propose a generative model to capture the dynamics of survival analysis,…

Physics and Society · Physics 2015-09-30 Trevor Fenner , Mark Levene , George Loizou

In this paper, a brief review of delay population models and their applications in ecology is provided. The inclusion of diffusion and nonlocality terms in delay models has given more capabilities to these models enabling them to capture…

Populations and Evolution · Quantitative Biology 2017-01-18 Majid Bani-Yaghoub

Existence of different kinds of synchronizations, namely anticipatory, complete and lag type synchronizations (both exact and approximate), are shown to be possible in time-delay coupled piecewise linear systems. We deduce stability…

Chaotic Dynamics · Physics 2009-11-11 D. V. Senthilkumar , M. Lakshmanan

A new type of nonstationary Gaussian process model is developed for approximating computationally expensive functions. The new model is a composite of two Gaussian processes, where the first one captures the smooth global trend and the…

Applications · Statistics 2013-01-14 Shan Ba , V. Roshan Joseph

This paper investigates the theoretical behavior of generative models under finite training populations. Within the stochastic interpolation generative framework, we derive closed-form expressions for the optimal velocity field and score…

Machine Learning · Computer Science 2025-09-29 Yunchen Li , Shaohui Lin , Zhou Yu