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

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We propose a Bayesian nonparametric mixture model for prediction- and information extraction tasks with an efficient inference scheme. It models categorical-valued time series that exhibit dynamics from multiple underlying patterns (e.g.…

Machine Learning · Statistics 2017-06-21 Jan Reubold , Thorsten Strufe , Ulf Brefeld

We propose martingale consumption as a natural, desirable consumption pattern for any given (proportional) investment strategy. The idea is to always adjust current consumption so as to achieve level expected future consumption under the…

Mathematical Finance · Quantitative Finance 2025-05-28 Peter Holm Nielsen

This paper is a close follow-up of Kaltenbacher and Tomba 2013 and Jin 2012, where Newton-Landweber iterations have been shown to converge either (unconditionally) without rates or (under an additional regularity assumption) with rates. The…

Numerical Analysis · Mathematics 2014-08-22 Barbara Kaltenbacher , Ivan Tomba

An analytic model is presented that considers the evolution of a market of durable goods. The model suggests that after introduction goods spread always according to a Bass diffusion. However, this phase will be followed by a diffusion…

General Finance · Quantitative Finance 2013-06-17 Joachim Kaldasch

A novel mathematical framework is proposed to describe the ecological and evolutionary consequences of consumer--resource interactions. Both the consumer and resource are assumed to consist of several (sub)species, which interact between…

Populations and Evolution · Quantitative Biology 2025-11-11 Alexander S. Bratus , Sergei V. Drozhzhin , Artem S. Novozhilov

We obtain variants of the classical von Neumann-Morgenstern expected utility theorem, with and without the completeness axiom, in which the derived Bernoulli utility functions are Lipschitz. The prize space in these results is an arbitrary…

Functional Analysis · Mathematics 2021-04-23 Efe A. Ok , Nik Weaver

In this work, a sampled-data nonlinear observer is designed using a continuous-time design coupled with an inter-sample output predictor. The proposed sampled-data observer is a hybrid system. It is shown that under certain conditions, the…

Optimization and Control · Mathematics 2008-02-01 Iasson Karafyllis , Costas Kravaris

Penalized regression models are popularly used in high-dimensional data analysis to conduct variable selection and model fitting simultaneously. Whereas success has been widely reported in literature, their performances largely depend on…

Machine Learning · Statistics 2013-12-16 Wei Sun , Junhui Wang , Yixin Fang

Recent work on mutation-selection models has revealed that, under specific assumptions on the fitness function and the mutation rates, asymptotic estimates for the leading eigenvalue of the mutation-reproduction matrix may be obtained…

Populations and Evolution · Quantitative Biology 2007-05-23 E. Baake , M. Baake , A. Bovier , M. Klein

Classification of sequence data is the topic of interest for dynamic Bayesian models and Recurrent Neural Networks (RNNs). While the former can explicitly model the temporal dependencies between class variables, the latter have a capability…

Machine Learning · Computer Science 2018-03-12 Son N. Tran , Srikanth Cherla , Artur Garcez , Tillman Weyde

Matrix valued data has become increasingly prevalent in many applications. Most of the existing clustering methods for this type of data are tailored to the mean model and do not account for the dependence structure of the features, which…

Machine Learning · Statistics 2023-12-07 Inbeom Lee , Siyi Deng , Yang Ning

To choose between two discrete goods, a consumer pays attention to only those with prices below a threshold. From these, she chooses her most preferred good. We assume consumers in a population have the same preference but may have…

Theoretical Economics · Economics 2025-11-07 Kaushil Patel

Model-based clustering integrated with variable selection is a powerful tool for uncovering latent structures within complex data. However, its effectiveness is often hindered by challenges such as identifying relevant variables that define…

Estimating consumer preferences is central to many problems in economics and marketing. This paper develops a flexible framework for learning individual preferences from partial ranking information by interpreting observed rankings as…

Machine Learning · Statistics 2026-02-19 Yu-Chang Chen , Chen Chian Fuh , Shang En Tsai

We consider the evolution of populations under the joint action of mutation and differential reproduction, or selection. The population is modelled as a finite-type Markov branching process in continuous time, and the associated…

Populations and Evolution · Quantitative Biology 2009-02-23 Ellen Baake , Hans-Otto Georgii

We introduce LemonadeBench v0.5, a minimal benchmark for evaluating economic intuition, long-term planning, and decision-making under uncertainty in large language models (LLMs) through a simulated lemonade stand business. Models must…

General Finance · Quantitative Finance 2026-02-18 Aidan Vyas

Survival analysis is an important area of medical research, yet existing models often struggle to balance simplicity with flexibility. Simple models require minimal adjustments but come with strong assumptions, while more flexible models…

Methodology · Statistics 2025-08-22 Peter Knaus , Daniel Winkler , Sebastian F. Schoppmann , Gerd Jomrich

Clustered observations are ubiquitous in controlled and observational studies and arise naturally in multi-centre trials or longitudinal surveys. We present a novel model for the analysis of clustered observations where the marginal…

Methodology · Statistics 2022-11-03 Luisa Barbanti , Torsten Hothorn

Boltzmann machines (BMs) are powerful energy-based generative models, but their heavy training cost has largely confined practical use to Restricted BMs (RBMs) trained with an efficient learning method called contrastive divergence. More…

Machine Learning · Computer Science 2025-12-03 Kentaro Kubo , Hayato Goto

We provide a continuous time limit analysis for the class of Ensemble Square Root Filter algorithms with deterministic model perturbations. In the particular linear case, we specify general conditions on the model perturbations implying…

Probability · Mathematics 2021-12-21 Theresa Lange , Wilhelm Stannat