二层随机规划逼近解的收敛性

对二层随机规划的逼近解的收敛性作了探讨,证明了当随机向量序列{ζ(k)(w)}依分布收敛于ζ(w)时,相应于ζ(k)(w)的二层随机规划问题的任何最优解序列将收敛到原问题的最优解.     

关于k阶记录时间与k阶记录值的联合分布

设独立同分布随机变量序列{x_nj n≥1}的分布函数F(x)=p(x₁(k)(n);n≥1},{X^(k)(n);n≥1} 分别为{x_nj n≥1}的K阶记录时间序列和k阶记录值序列.本文我们用直接方法求出了{U^(k)(i),X^(k)(i);1≤i≤n}的联合分布，从而证明了k阶记录时间序列及k阶记录值序列的马氏性，并导出了它们之间的一     

带随机消费的经济模型

本文探讨了非生产性消费对生产发展的影响，在假设{Λ^-(n)(ω)}n≥1为独立随机向量族的条件下，给出了最大产出Y^(n)(ω)分布由{Λ^(j)(ω)}1≤j≤n的分布决定的结论。     

一个定理的加强和猜想

文[1]中的定理2为:数列{an}满足an 2=pan 1-an,且p=2cos2πk(k>2,k∈N ),则k是它的一个周期.对该定理我们可作进一步加强得:定理不全为零的数列{an}满足an 2=pan 1-an,且p=2cos2πk(k>2,k∈N ).则该数列具有周期性,且最小正周期为k.证明数列{an}是线性递推数列,则特征方程为x2-     

A note on Sobolev orthogonality for Laguerre matrix polynomials

Let {Ln(A,λ)(x)}n≥0 be the sequence of monic Laguerre matrix polynomials defined on [0, ∞) by Ln(A,λ)(x)=n!/(-λ)n∑nk=0(-λ)κ/k!(n-1)! (A I)n[(A I)k]-1 xk,where A ∈ Cr×r. It is known that {Ln(A,λ)(x)}n≥0 is orthogonal with respect to a matrix moment functional when A satisfies the spectral condition that Re(z) ＞ - 1 for every z ∈σ(A).In this note we show that forA such that σ(A) does not contain negative integers, the Laguerre matrix polynomials Ln(A,λ) (x) are orthogonal with respect to a non-diagonal SobolevLaguerre matrix moment functional, which extends two cases: the above matrix case and the known scalar case.     

有关Euler函数(n)的方程的正整数解

设(n)是Euler函数.主要研究了方程(xy)=3((x)+(y))的可解性问题,利用初等的方法给出了这一方程的所有的35组正整数解.对于任意素数k>3,(x,y)=(3k,4k),(4k,3k)是方程(xy)=k((x)+(y))的2个正整数解.证明了更为一般的结论:对于任意奇数k>3,当gcd(k,3)=1时,(x,y)=(3k,4k),(4k,3k)是方程(xy)=k((x)+(y))的2个正整数解.     

带二阶导数的插值定理

用B_(δ,p)(1P∞)表示P次可积Fourier变換具有紧支集[-δ,δ]的带有限函数。证明了对于B_(3δ,p)中的函数,可以在L_p(R)尺度下,由序列{f(κπ/δ)},{f'(κπ/δ)}以及{f'(κπ/δ)}的Hermite型插值进行重构.     

有界平均振动亚纯函数的又一特征

在文献[1]和[2]中曾获得关于 Blaschke 商的如下结果:定理 A 设{a_n~(1))及{a_n~(2)}是 D={z:|z|<1}内两个不相交的插值序列。设 B_k(z)是以{a_n~(k))为零点的 Blaschke 乘积(k=1,2)。则下列三条件等价:(Ⅰ)B_1/B_2为正规函数。(Ⅱ){a_n~(1))∪{a_n~(2)}为插值序列。     

有限型的首次返回例外集的测度和维数北大核心CSCD

设M=(m_(ij))是一个b×b阶矩阵且m_(ij)∈{0,1},∑_(M)是矩阵M=(m_(ij))诱导产生的有限型,σ是其上左推移算子.本文主要研究的是有限型动力系统(∑_(M),σ)上的首次返回速度问题.令τ_(k)(x)是点x∈∑_(M)首次返回到包含x的k阶柱集时间,且E_(α,β)={x∈∑_(M):lim inf_(k→∞)(logτ_(k)(x))/k=α,lim sup_(k→∞)(logτ_(k)(x))/k=β}.我们证明了:当M是不可约矩阵时,对任意0≤α≤β≤+∞,集合E_(α,β)的Markov测度要么等于0要么等于1并且具有满的Hausdorff维数.     

非参数回归函数的基于截尾数据的估计

本文考虑截尾数据情况下非参数回归函数m(x)=E(Y|x)的估计。具体地讲,我们面对的是这样的数学模型:T是与(X,Y)独立的随机变量,我们观测到的不是Y本身,而是Z=min(Y,T)及δ=[Y≤T]。今有训练样本{(X_i,Z_i,δ_i)}_(i-1)及当前样本(X,z,δ),记ξ_i(·)=[z_i≥·], N~ (·)=sum from i=1 to n ξ_i(·), V_n(·)=multiply from i=1 to n{1 N~ (z_i)/2 N~ (z_i)}~[δ_i=_i<0], U_n(·)=sum from i=1 to n Wnt(x)ξ_i(·), 令 m_n(x)=integral from 0 to u_n U_n(y)|V_n(y)dy, 其中u_n=F_2~(-1)(n~(-a)),0<α<1/2为一实常数,F_2(·)=P(Y≥·)为Y的(右侧)分布函数。在权函数{W_(ni)(x)}_(i=1)~n及(X,Y,T)的分布函数满足一组条件下,我们证明了m_n(x)为m(x)的强相合估计,即:m_n(x)→m(x),a.s.(n→ ∞).     

负相协随机变量非随机和的差的精确大偏差

In this paper,we study precise large deviation for the non-random difference sum from j=1 to n_1(t) X_(1j)-sum from j=1 to n_2(t) X_(2j),where sum from j=1 to n_1(t) X_(1j) is the non-random sum of {X_(1j),j≥1} which is a sequence of negatively associated random variables with common distribution F_1(x),and sum from j=1 to n_2(t) X_(2j) is the non-random sum of {X_(2j),j≥1} which is a sequence of independent and identically distributed random variables,n_1(t) and n_2(t) are two positive integer functions.Under some other mild conditions,we establish the following uniformly asymptotic relation lim t→∞ sup x≥r(n_1(t))~(p+1)|(P(∑~(n_1(t)_(j=1)X_(1j)-∑~(n_2(t)_(j=1)X_(2j)-(μ_1n_1(t)-μ_2n_2(t)x))/(n_1(t)F_1(x))-1|=0.     

On the Existence of Solutions for First Order Quasilinear Symmetrizable Systenis of Partial Differential Equations

In this paper we study the first order quasilinear symmetrizable system of partial differential equations $\sum\limits_{i = 1}^n {{a_i}(x,u)\frac{{\partial u}}{{\partial {x_i}}} + \lambda u = f(x,u)}$ (1) where a_i(x,y) are k*k matrices.     

关于等角写像的边界性质

<正> 一个函数f(x)在[a,b]上定义,我们记 f(x)∈H_x~a(0<α≤1),表示f(x)是满足α级 Lipschitz-H(?)lder 条件的函数,下标表示所涉及的自变量,而f(x)∈H_x~(1-0表示f(x)之连续模满足条件ω(δ,f)≤kδ|log δ|,(k为常数).我们记(?)是其连续模满足条件     

Буняковский不等式之推广及其对于积分方程与希尔伯特空间之应用

<正> 不等式■(1) 通常称为布湼可夫斯基不等式,或席瓦耳智不等式,在本文中,作者推广此不等式为这里我们用 det u_(ij)(i,j=1,2,…,n)表第i列j行之元为 u_(ij)之n列行列式,f_i,g_j(i,j=1,2,…,n)表任一希尔伯特空间之任意二组之元,(f_i,g_j)表f_i与g_j二元之内乘积.     

一类连续体上连续映射的周期点

设X是个阶有限的遗传可分解可链连续体, f:X→X是X上的连续自映射, On(x,f)={fi(x):0≤i≤n)是f的一个返回轨道, inf(On(x,f))相似文献   

Limit Distributions of Eigenvalues for Random Block Toeplitz and Hankel Matrices

Block Toeplitz and Hankel matrices arise in many aspects of applications. In this paper, we will research the distributions of eigenvalues for some models and get the semicircle law. Firstly we will give trace formulas of block Toeplitz and Hankel matrix. Then we will prove that the almost sure limit g_T^(m)\gamma_{T}^{(m)} (g_H^(m))(\gamma_{H}^{(m)}) of eigenvalue distributions of random block Toeplitz (Hankel) matrices exist and give the moments of the limit distributions where m is the order of the blocks. Then we will prove the existence of almost sure limit of eigenvalue distributions of random block Toeplitz and Hankel band matrices and give the moments of the limit distributions. Finally we will prove that g_T^(m)\gamma_{T}^{(m)} (g_H^(m))(\gamma_{H}^{(m)}) converges weakly to the semicircle law as m→∞.     

Random symmetric polynomials

Let {Q⁽ⁿ⁾(x₁,...,x_n)} be a sequence of symmetric polynomials having a fixed degree equal to k. Let {X_n1,...,X_nn}, n k, be some sequence of series of random variables (r.v.). We form the sequence of r.v. Y_n=Q⁽ⁿ⁾(X_n1, ... X_nn), n k One obtains limit theorems for the sequence Y_n, under very general assumptions.Translated from Veroyatnostnye Raspredeleniya i Matematicheskaya Statistika, pp. 170–188, 1986.     

Random ergodic theorems and real cocycles

We study mean convergence of ergodic averages associated to a measure-preserving transformation or flow τ along the random sequence of times κ _n (ω) given by the Birkhoff sums of a measurable functionF for an ergodic measure-preserving transformationT. We prove that the sequence (k _n(ω)) is almost surely universally good for the mean ergodic theorem, i.e., that, for almost every, ω, the averages (*) converge for every choice of τ, if and only if the “cocycle”F satisfies a cohomological condition, equivalent to saying that the eigenvalue group of the “associated flow” ofF is countable. We show that this condition holds in many natural situations. When no assumption is made onF, the random sequence (k _n(ω)) is almost surely universally good for the mean ergodic theorem on the class of mildly mixing transformations τ. However, for any aperiodic transformationT, we are able to construct an integrable functionF for which the sequence (k _n(ω)) is not almost surely universally good for the class of weakly mixing transformations.     

A Note on Randomly Weighted Sums of Dependent Subexponential Random Variables

The author obtains that the asymptotic relations■hold as x→∞,where the random weightsθ_1,···,θ_(n )are bounded away both from 0 and from∞with no dependency assumptions,independent of the primary random variables X_1,···,X_(n )which have a certain kind of dependence structure and follow non-identically subexponential distributions.In particular,the asymptotic relations remain true whenX_1,···,X_(n )jointly follow a pairwise Sarmanov distribution.     

Local Precise Large and Moderate Deviations for Sums of Independent Random Variables

Let {X, X_k : k ≥ 1} be a sequence of independent and identically distributed random variables with a common distribution F. In this paper, the authors establish some results on the local precise large and moderate deviation probabilities for partial sums S_n =sum from i=1 to n(X_i) in a unified form in which X may be a random variable of an arbitrary type,which state that under some suitable conditions, for some constants T 0, a and τ 1/2and for every fixed γ 0, the relation P(S_n- na ∈(x, x + T ]) ~nF((x + a, x + a + T ]) holds uniformly for all x ≥γn~τ as n→∞, that is, P(Sn- na ∈(x, x + T ]) lim sup- 1 = 0.n→+∞x≥γnτnF((x + a, x + a + T ])The authors also discuss the case where X has an infinite mean.