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Related papers: $\R \times BL^* $ Valued Consumer Resource Model

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Finite mixtures of regressions with fixed covariates are a commonly used model-based clustering methodology to deal with regression data. However, they assume assignment independence, i.e. the allocation of data points to the clusters is…

Methodology · Statistics 2021-04-27 Salvatore D. Tomarchio , Paul D. McNicholas , Antonio Punzo

We study how the complexity of evolutionary dynamics in the classic MacArthur consumer-resource model depends on resource uptake and utilization rates. The traditional assumption in such models is that the utilization rate of the consumer…

Populations and Evolution · Quantitative Biology 2019-10-18 Iaroslav Ispolatov , Michael Doebeli

This paper is devoted to the analysis of the long-time behavior of a phenotypic-structured model where phenotypic changes do not occur. We give a mathematical description of the process in which the best adapted trait is selected in a given…

Analysis of PDEs · Mathematics 2024-07-02 Shen Bian , Jiale Bu

Dworczak et al. (2021) study when certain market structures are optimal in the presence of heterogeneous preferences. A key assumption is that the social planner knows the joint distribution of the value of the good and marginal value of…

Theoretical Economics · Economics 2021-11-22 Roy Allen , John Rehbeck

We propose an automatable data-driven methodology for robust nonlinear reduced-order modelling from time-resolved snapshot data. In the kinematical coarse-graining, the snapshots are clustered into few centroids representable for the whole…

Fluid Dynamics · Physics 2020-12-02 Hao Li , Daniel Fernex , Richard Semaan , Jianguo Tan , Marek Morzyński , Bernd R. Noack

In this manuscript, we consider a finite nonparametric mixture model with non-independent marginal density functions. Dependence between the marginal densities is modeled using a copula device. Until recently, no deterministic algorithms…

Methodology · Statistics 2025-05-23 Michael Levine

We propose two approaches for selecting variables in latent class analysis (i.e.,mixture model assuming within component independence), which is the common model-based clustering method for mixed data. The first approach consists in…

Computation · Statistics 2017-03-08 Matthieu Marbac , Mohammed Sedki

This paper provides nonparametric identification results for random coefficient distributions in perturbed utility models. We cover discrete and continuous choice models. We establish identification using variation in mean quantities, and…

Econometrics · Economics 2020-03-03 Roy Allen , John Rehbeck

Choice modeling is at the core of understanding how changes to the competitive landscape affect consumer choices and reshape market equilibria. In this paper, we propose a fundamental characterization of choice functions that encompasses a…

Econometrics · Economics 2024-02-21 Amandeep Singh , Ye Liu , Hema Yoganarasimhan

The ability to uncover preferences from choices is fundamental for both positive economics and welfare analysis. Overwhelming evidence shows that choice is stochastic, which has given rise to random utility models as the dominant paradigm…

General Economics · Economics 2018-11-07 Carlos Alos-Ferrer , Ernst Fehr , Nick Netzer

The system of two resources $R_1$, $R_2$ and one consumer $C$ is investigated within the Rosenzweig-MacArthur model with Holling type II functional response. The rates $\beta_i$ of consumption of resources $i=1,2$ are coupled by the…

Physics and Society · Physics 2022-09-28 Przemysław Gawroński , Alfio Borzì , Krzysztof Kułakowski

Coarse-grained (CG) models provide an effective route to reducing the complexity of molecular simulations (MD), but conventional approaches depend heavily on long all-atom MD trajectories to adequately sample configurational space. This…

Chemical Physics · Physics 2025-10-28 Maximilian Stupp , P. S. Koutsourelakis

We consider an online model for recommendation systems, with each user being recommended an item at each time-step and providing 'like' or 'dislike' feedback. A latent variable model specifies the user preferences: both users and items are…

Machine Learning · Statistics 2025-04-29 Mina Karzand , Guy Bresler

We prove the well-posedness of a general evolution reaction-nonlocal diffusion problem under two sets of assumptions. In the first set, the main hypothesis is the Lipschitz continuity of the range kernel and the bounded variation of the…

Analysis of PDEs · Mathematics 2024-01-26 Gonzalo Galiano

In this paper, we consider a model called CHARME (Conditional Heteroscedastic Autoregressive Mixture of Experts), a class of generalized mixture of nonlinear nonparametric AR-ARCH time series. Under certain Lipschitz-type conditions on the…

Machine Learning · Statistics 2020-11-18 José G. Gómez García , Jalal Fadili , Christophe Chesneau

Self-consuming generative models have received significant attention over the last few years. In this paper, we study a self-consuming generative model with heterogeneous preferences that is a generalization of the model in Ferbach et al.…

Machine Learning · Statistics 2025-11-14 Hongru Zhao , Jinwen Fu , Tuan Pham

The paper exposes a non-parametric approach to latent and co-latent modeling of bivariate data, based upon alternating minimization of the Kullback-Leibler divergence (EM algorithm) for complete log-linear models. For categorical data, the…

Methodology · Statistics 2016-03-10 François Bavaud

The main objective of this paper is to develop a martingale-type solution to optimal consumption--investment choice problems ([Merton, 1969] and [Merton, 1971]) under time-varying incomplete preferences driven by externalities such as…

Mathematical Finance · Quantitative Finance 2025-01-14 Weixuan Xia

Using the KKM technique, we establish some existence results for variational-hemivariational inequalities involving monotone set valued mappings on bounded, closed and convex subsets in reflexive Banach spaces. We also derive several…

Classical Analysis and ODEs · Mathematics 2009-09-09 Nicusor Costea , Cezar Lupu

The Lipschitz constant of the map between the input and output space represented by a neural network is a natural metric for assessing the robustness of the model. We present a new method to constrain the Lipschitz constant of dense deep…

Machine Learning · Computer Science 2023-08-22 Ouail Kitouni , Niklas Nolte , Mike Williams