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共查询到20条相似文献，搜索用时 131 毫秒
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Let X_1,…,X,be a sequence of p-dimensional iid.random vectors with a commondistribution F(x).Denote the kernel estimate of the probability density of F(if it exists)by_n(x)=n~(-1)h~_n(-p)K((x-X_i)/h_n)Suppose that there exists a measurable function g(x)and h_n>0,h_n→0 such thatlim sup丨f_n(x)-g(x)丨=0 a.s.Does F(x)have a uniformly continuous density function f(x)and f(x)=g(x)?This paperdeals with the problem and gives a sufficient and necessary condition for generalp-dimensional case.  相似文献

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§1. Introduction and Main Results Let X_1, X_2, …, X_n be iid. Samples drawn from a population with distribution F and density f in R~1. The method using the kernel estimator f_n(x) to estimate, f(x) was suggested by Rosenblatt and Parzen, where  相似文献

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Let X_1,…,X_n be i.i.d,samples drawn from an one-dimenslonal,population withdensity f.Definef_n(x)=(na_n(x))~(1-) sum form i=1 to n K((X-X_i)/(a_n(x))).We study the strong convergence rate of f_n(x) to f(x)at a predetermined point x_o.Under some properly chosen conditions,for f(x_o) and g_n(x_o)proposed in [3],we havepointwisebywhere C_n is any sequence tending to ∞,and n approaches ∞.If f(x)is only assumed tobe continuous at x_o.Then f_n(x_o)may converges to f(x_o)arbitrarily slowly.  相似文献

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The modulus of a doubly connected domain is determined by a quotient of certain kernel functions, namely the Bergman kernel, the reduced Bergman kernel and the square of the Szegö kernel. These methods are more efficient than methods involving the curvature of the Bergman metric.  相似文献

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The Heisenberg group gives rise to the simplest interesting example of a subellipticoperator. The hear kernel for this operator is known in terms of Fourier transforms. Here this hear kernel is derived in a simpleminded way from standard theroems in mathematical physics. A formula is given relating this kernel to the heat kernel of a magnetic field and ageneralization is given for similar geometries  相似文献

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We study differentiability of functions in the reproducing kernel Hilbert space (RKHS) associated with a smooth Mercer-like kernel on the sphere. We show that differentiability up to a certain order of the kernel yields both, differentiability up to the same order of the elements in the series representation of the kernel and a series representation for the corresponding derivatives of the kernel. These facts are used to embed the RKHS into spaces of differentiable functions and to deduce reproducing properties for the derivatives of functions in the RKHS. We discuss compactness and boundedness of the embedding and some applications to Gaussian-like kernels.  相似文献

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In recent years several authors have investigated the use of smoothing methods for sparse multinomial data. In particular, Hall and Titterington (1987) studied kernel smoothing in detail. It is pointed out here that the bias of kernel estimates of probabilities for cells near the boundaries of the multinomial vector can dominate the mean sum of squared error of the estimator for most true probability vectors. Fortunately, boundary kernels devised to correct boundary effects for kernel regression estimators can achieve the same result for these estimators. Properties of estimates based on boundary kernels are investigated and compared to unmodified kernel estimates and maximum penalized likelihood estimates. Monte Carlo evidence indicates that the boundary-corrected kernel estimates usually outperform uncorrected kernel estimates and are quite competitive with penalized likelihood estimates.  相似文献

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《Applied Mathematical Modelling》2014,38(15-16):3822-3833
Smoothed particle hydrodynamics (SPH) is a popular meshfree Lagrangian particle method, which uses a kernel function for numerical approximations. The kernel function is closely related to the computational accuracy and stability of the SPH method. In this paper, a new kernel function is proposed, which consists of two cosine functions and is referred to as double cosine kernel function. The newly proposed double cosine kernel function is sufficiently smooth, and is associated with an adjustable support domain. It also has smaller second order momentum, and therefore it can have better accuracy in terms of kernel approximation. SPH method with this double cosine kernel function is applied to simulate a dam-break flow and water entry of a horizontal circular cylinder. The obtained SPH results agree very well with the experimental results. The double cosine kernel function is also comparatively studied with two frequently used SPH kernel functions, Gaussian and cubic spline kernel functions.  相似文献

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The paper is related to the norm estimate of Mercer kernel matrices.The lower and upper bound estimates of Rayleigh entropy numbers for some Mercer kernel matrices on[0,1]×[0,1]based on the Bernstein-Durrmeyer operator kernel ale obtained,with which and the approximation property of the Bernstein-Durrmeyer operator the lower and upper bounds of the Rayleigh entropy number and the l2-norm for general Mercer kernel matrices on[0,1]×[0,1]are provided.  相似文献

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