Nonparametric Kernel Bayes Smoothing on State Space

In this paper, we use the reproducing kernel Hilbert space method (RKHSM) for solving a boundary value problem for the second order Bratu’s differential equation.. Convergence

In particular, Proposition 2.1 tells you the size of a maximal collection of disjoint separating curves on S , as there is always a subgroup of rank rkK = rkI generated by Dehn

Since the data measurement work in the Lamb wave-based damage detection is not time consuming, it is reasonable that the density function should be estimated by using robust

BOUNDARY INVARIANTS AND THE BERGMAN KERNEL 153 defining function r = r F , which was constructed in [F2] as a smooth approx- imate solution to the (complex) Monge-Amp` ere

Abstract. Recently, the Riemann problem in the interior domain of a smooth Jordan curve was solved by transforming its boundary condition to a Fredholm integral equation of the

In Section 4, we establish parabolic Harnack principle and the two-sided estimates for Green functions of the finite range jump processes as well as H¨ older continuity of

Keywords and phrases: symmetric jump process, metric measure space, heat kernel estimate, stability, Dirichlet form, cut-o↵ Sobolev inequality, capacity, Faber-Krahn inequality,

In this paper, the Bayes estimates are obtained under the linear exponential (LINEX) loss, general entropy and squared error loss function using Lindley’s approximation technique