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Nonstationary Gaussian processes (GPs) are essential for modeling complex, locally heterogeneous spatial data. A common modeling approach is the spatial deformation method that warps the domain to recover isotropy. However, this static…

Machine Learning · Computer Science 2026-05-01 Minghao Gu , Weizhi Lin , Qiang Huang

We investigate a simple quantitative genetics model subjet to a gradual environmental change from the viewpoint of the phylogenies of the living individuals. We aim to understand better how the past traits of their ancestors are shaped by…

Probability · Mathematics 2021-04-22 Vincent Calvez , Benoît Henry , Sylvie Méléard , Viet Chi Tran

We introduce a nonstationary spatio-temporal statistical model for gridded data on the sphere. The model specifies a computationally convenient covariance structure that depends on heterogeneous geography. Widely used statistical models on…

Applications · Statistics 2016-02-25 Stefano Castruccio , Joseph Guinness

Many real-world spatio-temporal processes exhibit nonlinear dynamics that can often be described through stochastic partial differential equations. These models are flexible and scientifically motivated, however, implementing them in a…

Methodology · Statistics 2025-06-30 Madelyn Clinch , Jonathan R. Bradley

In a traditional Gaussian graphical model, data homogeneity is routinely assumed with no extra variables affecting the conditional independence. In modern genomic datasets, there is an abundance of auxiliary information, which often gets…

Methodology · Statistics 2023-08-16 Yabo Niu , Yang Ni , Debdeep Pati , Bani K. Mallick

The method of covariate adjustment is often used for estimation of population average treatment effects in observational studies. Graphical rules for determining all valid covariate adjustment sets from an assumed causal graphical model are…

Statistics Theory · Mathematics 2019-12-18 Andrea Rotnitzky , Ezequiel Smucler

We identify a new natural coalescent structure, which we call the seed-bank coalescent, that describes the gene genealogy of populations under the influence of a strong seed-bank effect, where "dormant forms" of individuals (such as seeds…

Probability · Mathematics 2016-08-10 Jochen Blath , Adrián González Casanova , Noemi Kurt , Maite Wilke-Berenguer

In population genetics, extant samples are usually used for inference of past population genetic forces. With the Kingman coalescent and the backward diffusion equation, inference of the marginal likelihood proceeds from an extant sample…

Populations and Evolution · Quantitative Biology 2020-04-03 Claus Vogl , Sandra Peer

In this paper, we consider the inverse problem of determining some coefficients within a coupled nonlinear parabolic system, through boundary observation of its non-negative solutions. In the physical setup, the non-negative solutions…

Analysis of PDEs · Mathematics 2024-04-23 Hongyu Liu , Catharine W. K. Lo

We present a novel Bayesian nonparametric regression model for covariates X and continuous, real response variable Y. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the…

Methodology · Statistics 2015-06-25 Tristan Gray-Davies , Chris Holmes , Francois Caron

Sweepstakes reproduction may be generated by chance matching of reproduction with favorable environmental conditions. Gene genealogies generated by sweepstakes reproduction are in the domain of attraction of multiple-merger coalescents…

Probability · Mathematics 2026-01-15 Bjarki Eldon

We consider population modelling using parametrised ordinary differential equation initial value problems (ODE-IVPs). For each individual drawn randomly from the unknown population distribution, the corresponding parameters for the ODE-IVP…

Statistics Theory · Mathematics 2024-09-18 Han Cheng Lie

Consider a structured population consisting of $d$ colonies, with migration rates proportional to a positive parameter $K$. We sample $N_K$ individuals, distributed evenly across the $d$ colonies, and trace their ancestral lineages backward…

Probability · Mathematics 2026-01-27 Fernando Cordero , Sophia-Marie Mellis , Emmanuel Schertzer

We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(alpha) random variables, normalized by their sum, including beta-size-biasing on total length effects (beta < alpha). Depending on the range of alpha,…

Probability · Mathematics 2013-02-26 Thierry Huillet

We develop a continuous mathematical model of population dynamics that describes the sequential emergence of new genotypes under limited resources. The framework models genotype density as a nonlinear flow in mutation space, combining…

Populations and Evolution · Quantitative Biology 2025-12-10 Alexander Bratus , Tatiana Yakushkina , Vladimir Posvyanski

Though Gaussian graphical models have been widely used in many scientific fields, relatively limited progress has been made to link graph structures to external covariates. We propose a Gaussian graphical regression model, which regresses…

Methodology · Statistics 2022-02-01 Jingfei Zhang , Yi Li

We consider a class of evolution equations describing population dynamics in the presence of a carrying capacity depending on the population with delay. In an earlier work, we presented an exhaustive classification of the logistic equation…

Populations and Evolution · Quantitative Biology 2015-06-19 V. I. Yukalov , E. P. Yukalova , D. Sornette

Convective counterparts of variants of the nonlinear Fisher equation which describes reaction diffusion systems in population dynamics are studied with the help of an analytic prescription and shown to lead to interesting consequences for…

Populations and Evolution · Quantitative Biology 2007-05-23 Ignacio D. Peixoto , Luca Giuggioli , V. M. Kenkre

Evolution occurs in populations of reproducing individuals. The structure of a biological population affects which traits evolve. Understanding evolutionary game dynamics in structured populations is difficult. Precise results have been…

Populations and Evolution · Quantitative Biology 2017-08-16 Benjamin Allen , Gabor Lippner , Yu-Ting Chen , Babak Fotouhi , Naghmeh Momeni , Martin A. Nowak , Shing-Tung Yau

Accurate representation of non-Gaussian distributions of quantities of interest in nonlinear dynamical systems is critical for estimation, control, and decision-making, but can be challenging when forward propagations are expensive to carry…

Optimization and Control · Mathematics 2026-04-13 Aaron R. Liao , Kenshiro Oguri , Michele D. Carpenter