8,169 research outputs found

    A non-parametric method to nowcast the Euro Area IPI

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    Non-parametric methods have been empirically proved to be of great interest in the statistical literature in order to forecast stationary time series, but very few applications have been proposed in the econometrics literature. In this paper, our aim is to test whether non-parametric statistical procedures based on a Kernel method can improve classical linear models in order to nowcast the Euro area manufacturing industrial production index (IPI) by using business surveys released by the European Commission. Moreover, we consider the methodology based on bootstrap replications to estimate the confidence interval of the nowcasts.Non-parametric, Kernel, nowcasting, bootstrap, Euro area IPI.

    Entropy, Duality and Cross Diffusion

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    This paper is devoted to the use of the entropy and duality methods for the existence theory of reaction-cross diffusion systems consisting of two equations, in any dimension of space. Those systems appear in population dynamics when the diffusion rates of individuals of two species depend on the concentration of individuals of the same species (self-diffusion), or of the other species (cross diffusion)

    Enhanced Lasso Recovery on Graph

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    This work aims at recovering signals that are sparse on graphs. Compressed sensing offers techniques for signal recovery from a few linear measurements and graph Fourier analysis provides a signal representation on graph. In this paper, we leverage these two frameworks to introduce a new Lasso recovery algorithm on graphs. More precisely, we present a non-convex, non-smooth algorithm that outperforms the standard convex Lasso technique. We carry out numerical experiments on three benchmark graph datasets

    An accurate scheme to solve cluster dynamics equations using a Fokker-Planck approach

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    We present a numerical method to accurately simulate particle size distributions within the formalism of rate equation cluster dynamics. This method is based on a discretization of the associated Fokker-Planck equation. We show that particular care has to be taken to discretize the advection part of the Fokker-Planck equation, in order to avoid distortions of the distribution due to numerical diffusion. For this purpose we use the Kurganov-Noelle-Petrova scheme coupled with the monotonicity-preserving reconstruction MP5, which leads to very accurate results. The interest of the method is highlighted on the case of loop coarsening in aluminum. We show that the choice of the models to describe the energetics of loops does not significantly change the normalized loop distribution, while the choice of the models for the absorption coefficients seems to have a significant impact on it

    The regularity of the boundary of a multidimensional aggregation patch

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    Let d≥2d \geq 2 and let N(y)N(y) be the fundamental solution of the Laplace equation in RdR^d We consider the aggregation equation ∂ρ∂t+div⁡(ρv)=0,v=−∇N∗ρ \frac{\partial \rho}{\partial t} + \operatorname{div}(\rho v) =0, v = -\nabla N * \rho with initial data ρ(x,0)=χD0\rho(x,0) = \chi_{D_0}, where χD0\chi_{D_0} is the indicator function of a bounded domain D0⊂Rd.D_0 \subset R^d. We now fix 0<γ<10 < \gamma < 1 and take D0D_0 to be a bounded C1+γC^{1+\gamma} domain (a domain with smooth boundary of class C1+γC^{1+\gamma}). Then we have Theorem: If D0D_0 is a C1+γC^{1 + \gamma} domain, then the initial value problem above has a solution given by ρ(x,t)=11−tχDt(x),x∈Rd,0≤t<1\rho(x,t) = \frac{1}{1 -t} \chi_{D_t}(x), \quad x \in R^d, \quad 0 \le t < 1 where DtD_t is a C1+γC^{1 + \gamma} domain for all 0≤t<10 \leq t < 1
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