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This paper studies multi-agent systems with nonlinear consensus protocols, i.e., only nonlinear measurements of the states are available to agents. The solutions of these systems are understood in Filippov sense since the possible…

Optimization and Control · Mathematics 2017-04-12 Jieqiang Wei , Xinlei Yi , Henrik Sandberg , Karl Henrik Johansson

The Daniell-Kolmogorov Extension Theorem is a fundamental result in the theory of stochastic processes, as it allows one to construct a stochastic process with prescribed finite-dimensional distributions. However, it is well-known that the…

Probability · Mathematics 2023-01-20 Alexander Erreygers , Jasper De Bock

In this paper, we study mixed power-exponential moment functionals of nonlinearly perturbed semi-Markov processes in discrete time. Conditions under which the moment functionals of interest can be expanded in asymptotic power series with…

Probability · Mathematics 2016-04-28 Mikael Petersson

We derive sufficient conditions for the solvability of the state estimation problem for a class of nonlinear control time-varying systems which includes those, whose dynamics have triangular structure. The state estimation is exhibited by…

Optimization and Control · Mathematics 2018-06-07 John Tsinias , Constantinos Kitsos

It is rigorously proved that quasilinear impulsive systems possess unpredictable solutions when a perturbation generated by an unpredictable sequence is applied. The existence, uniqueness, as well as asymptotic stability of such solutions…

Dynamical Systems · Mathematics 2021-11-03 Mehmet Onur Fen , Fatma Tokmak Fen

This paper investigates conditional specifications for multivariate count variables. Recently, the spatial count data literature has proposed several conditional models such that the conditional expectations are linear in the conditioning…

Statistics Theory · Mathematics 2025-02-28 Yang Lu , Wei Sun

A novel approach to the problem of partial state estimation of nonlinear systems is proposed. The main idea is to translate the state estimation problem into one of estimation of constant, unknown parameters related to the systems initial…

Systems and Control · Computer Science 2016-04-08 Ortega Romeo , Bobtsov Alexey , Pyrkin Anton , Aranovskiy Stanislav

Based on the Chernoff approximation, we provide a general approximation result for convex monotone semigroups which are continuous w.r.t. the mixed topology on suitable spaces of continuous functions. Starting with a family $(I(t))_{t\geq…

Probability · Mathematics 2024-10-29 Jonas Blessing , Michael Kupper

The notion of asymptotic unpredictability was recently introduced in (Commun. Nonlinear Sci. Numer. Simul. 134, 108029, 2024) for semiflows. Likewise unpredictable trajectories, asymptotically unpredictable ones are also capable of…

Dynamical Systems · Mathematics 2024-10-08 Mehmet Onur Fen , Fatma Tokmak Fen

We obtain approximation results for general positive linear operators satisfying mild conditions, when acting on discontinuous functions and absolutely continuous functions having discontinuous derivatives. The upper bounds, given in terms…

Probability · Mathematics 2024-10-29 José A. Adell , P. Garrancho , F. J. Martínez-Sánchez

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a diffusion with uncertain local characteristics. Here, the differential characteristics are prescribed by a set-valued function. We establish…

Probability · Mathematics 2023-08-04 David Criens , Lars Niemann

Reinforced processes are known to provide a stochastic representation for the quasi-stationary distribution of a given killed Markov process - describing the killed Markov process at fixed time instants. In this paper we shall adapt the…

Probability · Mathematics 2022-02-10 Oliver Tough

The aim of this paper is investigating the existence of solutions of some semilinear elliptic problems on open bounded domains when the nonlinearity is subcritical and asymptotically linear at infinity and there is a perturbation term which…

Analysis of PDEs · Mathematics 2012-01-06 R. Bartolo , A. M. Candela , A. Salvatore

This paper develops a general theory on rates of convergence of penalized spline estimators for function estimation when the likelihood functional is concave in candidate functions, where the likelihood is interpreted in a broad sense that…

Statistics Theory · Mathematics 2021-05-14 Jianhua Z. Huang , Ya Su

In this article, we construct semiparametrically efficient estimators of linear functionals of a probability measure in the presence of side information using an easy empirical likelihood approach. We use estimated constraint functions and…

Methodology · Statistics 2023-03-01 Shan Wang , Hanxiang Peng

In this paper we present elementary computations for some Markov modulated counting processes, also called counting processes with regime switching. Regime switching has become an increasingly popular concept in many branches of science. In…

Probability · Mathematics 2023-02-27 Michel Mandjes , Peter Spreij

In this paper, we consider the sublinear expectation on bounded random variables. With the notion of uncorrelatedness for random variables under the sublinear expectation, a weak law of large numbers is obtained. With the notion of…

Probability · Mathematics 2023-11-17 Wenhao Li , Chuanfeng Sun

In this paper, we obtain a new estimate for uniform integrability under sublinear expectations. Based on this, we establish the limit theorems under nonlinear expectations dominated by sublinear expectations through tightness, and the limit…

Probability · Mathematics 2025-06-23 Xiaojuan Li , Mingshang Hu

The average treatment effect can obscure important heterogeneity when individuals respond differently to a treatment. While the conditional average treatment effect (CATE) function captures such heterogeneity, it is difficult to communicate…

Methodology · Statistics 2026-05-18 Anders Munch , Thomas A. Gerds

Euclidean Markov decision processes are a powerful tool for modeling control problems under uncertainty over continuous domains. Finite state imprecise, Markov decision processes can be used to approximate the behavior of these infinite…

Artificial Intelligence · Computer Science 2020-06-29 Manfred Jaeger , Giorgio Bacci , Giovanni Bacci , Kim Guldstrand Larsen , Peter Gjøl Jensen