This study examines the influence of oil shocks on systemic risk spillover among the commodity ***,this paper uses the DCC-GARCH approach combined with the TVP-VAR model to calculate risk connectedness and the GARCH-M...
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This study examines the influence of oil shocks on systemic risk spillover among the commodity ***,this paper uses the DCC-GARCH approach combined with the TVP-VAR model to calculate risk connectedness and the GARCH-MIDAS model to explore how oil shocks from different sources affect the risk spillover effects among the commodity *** results are the following:First,there are significant risk spillovers among the commodity markets with important time-varying characteristics and with sharp changes in times of *** industrial metals,agriculture,precious metals,and light energy commodity markets are risk recipients,and the energy and livestock commodity markets are risk ***,oil price shocks,particularly oil aggregate demand shocks,prominently affect the total risk connectedness among the commodity *** particular,the impact on the net risk spillover effect of different commodity market differs.
In this paper, we propose a high-order finite volume method for solving multicomponent fluid problems. Our method couples the quasi-conservative form with the reconstruction of conservative variables in a characterist...
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In this paper, we propose a high-order finite volume method for solving multicomponent fluid problems. Our method couples the quasi-conservative form with the reconstruction of conservative variables in a characteristic manner. The source term and numerical fluxes are carefully designed to maintain the pressure and velocity equilibrium for the interface-only problem and preserve the equilibrium of physical parameters in a single-component fluid. These ingredients enable our scheme to achieve both high-order accuracy in the smooth region and the high resolution in the discontinuity region of the solution. Extensive numerical tests are performed to verify the high resolution and accuracy of the scheme.
Trustworthy ML systems should not only return accurate predictions, but also a reliable representation of their uncertainty. Bayesian methods are commonly used to quantify both aleatoric and epistemic uncertainty, but...
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Trustworthy ML systems should not only return accurate predictions, but also a reliable representation of their uncertainty. Bayesian methods are commonly used to quantify both aleatoric and epistemic uncertainty, but alternative approaches, such as evidential deep learning methods, have become popular in recent years. The latter group of methods in essence extends empirical risk minimization (ERM) for predicting second-order probability distributions over outcomes, from which measures of epistemic (and aleatoric) uncertainty can be extracted. This paper presents novel theoretical insights of evidential deep learning, highlighting the difficulties in optimizing second-order loss functions and interpreting the resulting epistemic uncertainty measures. With a systematic setup that covers a wide range of approaches for classification, regression and counts, it provides novel insights into issues of identifiability and convergence in second-order loss minimization, and the relative (rather than absolute) nature of epistemic uncertainty measures. Copyright 2024 by the author(s)
Continuous state nonhomogeneous Markov chains are widely used to model the performance of random variables continuously varied over time in many fields such as population *** works mainly focus on their strong law of ...
Continuous state nonhomogeneous Markov chains are widely used to model the performance of random variables continuously varied over time in many fields such as population *** works mainly focus on their strong law of large numbers. There is little work developed on their limit theorems. To this end, this paper investigates the limiting properties of continuous state nonhomogeneous Markov chains, and establishes limit theorems for multivariate functions of continuous state nonhomogeneous Markov chains, including the strong law of lager numbers, the central limit theorem and almost sure central limit theorem under some mild conditions, which are some basic theoretical properties for statistical inference and predictions of continuous-time-varying random variables.
This paper is intended to investigate a class of Nicholson's blowflies system with patch structure and multiple pairs of distinct time-varying delays,we are interested in finding the infuence of the distinct time-...
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This paper is intended to investigate a class of Nicholson's blowflies system with patch structure and multiple pairs of distinct time-varying delays,we are interested in finding the infuence of the distinct time-varying delays in the same reproductive function on its asymptotic *** using the theory of functional differential equations,the fluctuation lemma,and the technique of differential inequalities,some new delay-dependent criteria on the global attractivity of the positive equilibrium point are *** addition,the effectiveness and feasibility of the theoretical achievements are illustrated by some numerical simulations.
Let(Z_(n))be a supercritical bisexual branching process in a random environmentξ.We study the almost sure(a.s.)convergence rate of the submartingale W_(n)=Z_(n)/In to its limit W,where(In)is an usually used norming *...
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Let(Z_(n))be a supercritical bisexual branching process in a random environmentξ.We study the almost sure(a.s.)convergence rate of the submartingale W_(n)=Z_(n)/In to its limit W,where(In)is an usually used norming *** prove that under a moment condition of order p∈(1,2),W-W_(n)=o(e^(-na))*** some a>0 that we find explicitly;assuming the logarithmic moment condition holds,we haveW-W_(n)=o(n^(-α))a.s..In order to obtain these results,we provide the L^(p)-convergence of(W_(n));similar conclusions hold for a bisexual branching process in a varying environment.
We model the Darmstadt Slip Length Tribometer (SLT) originally presented by Pelz et al. [1]. The plate tribometer is specially designed to measure viscosity and slip length simultaneously for lubrication gaps in the r...
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Numerical simulation of wetting and dewetting of geometrically complex surfaces benefits from the boundary-fitted unstructured Finite Volume method because it discretizes boundary conditions on geometrically complex d...
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Three-way conflict analysis typically investigates conflict situations by analyzing the trisection of agent pairs, agents, and issues from the perspectives of either conflict or alliance. However, in fuzzy conflict si...
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