In this paper we discuss a step further some convergence and continuity problems of distribution function on R^i. We give the following results: (1)distribution function F(x_1,…,x_k) on R^k is continuous if and only ...In this paper we discuss a step further some convergence and continuity problems of distribution function on R^i. We give the following results: (1)distribution function F(x_1,…,x_k) on R^k is continuous if and only if all marginal distribution functions of F is continuous on R^1. (2)If limF_n(x_1,……,x_k)=F(x_1,…,x_k) and limF_n(x_1—0,…,x_k—0)=F(x_1—0,…,x_k—0) at all non-continuity points of F, then展开更多
The roughness of the model function f（x） to the basis functions has been identified. When the model function is continuous segment, its roughness does not depend on the behavior of the first segment, but depends on ...The roughness of the model function f（x） to the basis functions has been identified. When the model function is continuous segment, its roughness does not depend on the behavior of the first segment, but depends on ＂h＂, the shift in the slope of two consecutive segments. If the distribution of design is uniform, f（x） is continuous segment function, and h is constant, then the maximum roughness is h2/192 obtained at the midpoint of the observations. Suppose that we have a sequence of designs {Pn（x）} then its corresponding distribution {Fn （x）} converges weakly to some distribution F（x）. Let D（f） be a set of discontinuous points off（x）, it is possible to take the limit of the roughness if D（f） has zero （dF）-measure. The behavior of maximum roughness of the discontinuous segment function has been studied by using grid points.展开更多
With the notion of independent identically distributed(IID) random variables under sublinear expectations introduced by Peng,we investigate moment bounds for IID sequences under sublinear expectations. We obtain a mom...With the notion of independent identically distributed(IID) random variables under sublinear expectations introduced by Peng,we investigate moment bounds for IID sequences under sublinear expectations. We obtain a moment inequality for a sequence of IID random variables under sublinear expectations. As an application of this inequality,we get the following result:For any continuous functionsatisfying the growth condition |(x) | C(1 + |x|p) for some C > 0,p 1 depending on ,the central limit theorem under sublinear expectations obtained by Peng still holds.展开更多
In this paper we consider the problem of estimation of a continuous distribution function under the LINEX loss function. The best invariant estimator is obtained and proved to be minimax for any sample size n ≥ 1.
This paper contains a study of propagation of singular travelling waves u（x, t） for conservation laws ut ＋ [Ф（u）]x = ψ（u）, where Ф, ψ are entire functions taking real values on the real axis. Conditions for...This paper contains a study of propagation of singular travelling waves u（x, t） for conservation laws ut ＋ [Ф（u）]x = ψ（u）, where Ф, ψ are entire functions taking real values on the real axis. Conditions for the propagation of wave profiles β ＋ mδ and β ＋ mδt are presented （β is a real continuous function, m ≠ 0 is a real number and δ＇ is the derivative of the Dirac measure 5）. These results are obtained with a consistent concept of solution based on our theory of distributional products. Burgers equation ut ＋ （u2/2）x = 0, the iffusionless Burgers-Fischer equation ut ＋ a（u2/2）x = ru（1 - u/k） with a, r, k being positive numbers, Leveque and Yee equation ut ＋ ux = μx（1 - u）（u - u/k） with μ ≠ 0, and some other examples are studied within such a setting. A ＂tool box＂ survey of the distributional products is also included for the sake of completeness.展开更多
文摘In this paper we discuss a step further some convergence and continuity problems of distribution function on R^i. We give the following results: (1)distribution function F(x_1,…,x_k) on R^k is continuous if and only if all marginal distribution functions of F is continuous on R^1. (2)If limF_n(x_1,……,x_k)=F(x_1,…,x_k) and limF_n(x_1—0,…,x_k—0)=F(x_1—0,…,x_k—0) at all non-continuity points of F, then
文摘The roughness of the model function f（x） to the basis functions has been identified. When the model function is continuous segment, its roughness does not depend on the behavior of the first segment, but depends on ＂h＂, the shift in the slope of two consecutive segments. If the distribution of design is uniform, f（x） is continuous segment function, and h is constant, then the maximum roughness is h2/192 obtained at the midpoint of the observations. Suppose that we have a sequence of designs {Pn（x）} then its corresponding distribution {Fn （x）} converges weakly to some distribution F（x）. Let D（f） be a set of discontinuous points off（x）, it is possible to take the limit of the roughness if D（f） has zero （dF）-measure. The behavior of maximum roughness of the discontinuous segment function has been studied by using grid points.
基金supported in part by National Basic Research Program of China (973 Program) (Grant No. 2007CB814901)the Natural Science Foundation of Shandong Province (Grant No. ZR2009AL015)
文摘With the notion of independent identically distributed(IID) random variables under sublinear expectations introduced by Peng,we investigate moment bounds for IID sequences under sublinear expectations. We obtain a moment inequality for a sequence of IID random variables under sublinear expectations. As an application of this inequality,we get the following result:For any continuous functionsatisfying the growth condition |(x) | C(1 + |x|p) for some C > 0,p 1 depending on ,the central limit theorem under sublinear expectations obtained by Peng still holds.
基金This research is supported by National Natural Science Foundation of China （No. 10571070）.
文摘In this paper we consider the problem of estimation of a continuous distribution function under the LINEX loss function. The best invariant estimator is obtained and proved to be minimax for any sample size n ≥ 1.
基金supported by Fundac ao para a Ci encia e a Tecnologia,PEst OE/MAT/UI0209/2011
文摘This paper contains a study of propagation of singular travelling waves u（x, t） for conservation laws ut ＋ [Ф（u）]x = ψ（u）, where Ф, ψ are entire functions taking real values on the real axis. Conditions for the propagation of wave profiles β ＋ mδ and β ＋ mδt are presented （β is a real continuous function, m ≠ 0 is a real number and δ＇ is the derivative of the Dirac measure 5）. These results are obtained with a consistent concept of solution based on our theory of distributional products. Burgers equation ut ＋ （u2/2）x = 0, the iffusionless Burgers-Fischer equation ut ＋ a（u2/2）x = ru（1 - u/k） with a, r, k being positive numbers, Leveque and Yee equation ut ＋ ux = μx（1 - u）（u - u/k） with μ ≠ 0, and some other examples are studied within such a setting. A ＂tool box＂ survey of the distributional products is also included for the sake of completeness.
