相依样本下移动平滑过程的极限性质(英文)

定义平滑过程{Xn=∑i=-∞∞aiYi+n;n≥1},其中{ai;-∞i∞}是绝对可和的实数序列,{Yi;-∞i∞}是独立同分布并且-ρ-混合的双边无限序列.在{Yi;-∞i∞}均值为零、方差有限等条件下,证明移动平滑过程的收敛性,推广了李和张的结论.     

负相伴样本平滑移动过程的完全收敛性

设{Y，Yi，-∞＜i＜∞}为一负相伴同分布随机变量序列，{ai，-∞＜i＜∞}绝对可和的实数序列，本文在适当的条件下，证明了平滑移动过程{∑k=1^n∑i=-∞^∞ai k Yi/n^1/t,n≥1}的完全收敛性．所得的结果改进了[1]中的定理1．     

负相关样本平滑移动过程的矩完全收敛性(英文)

本文研究了负相关样本平滑移动过程Xk=∑∞i=-∞ai+kYi的矩完全收敛性,这里{Yi,-∞相似文献   

负相依样本平滑移动过程的完全收敛性

设{Yi;－∞＜i＜∞}为一负相伴的同分布随机变量序列，{ai；－∞＜i＜∞}为绝对可和的实数序列。本文在适当的条件下。证明了平滑移动过程{∑k=1^n∑i=-∞^∞ai kYi/n^1/t;n≥1}的完全收敛性。     

α-混合随机序列最近邻密度估计的强相合收敛速度

设{Xi）i=1^∞是一维平稳序列，具有公共的未知密度f（x），在{Xi}i=1^∞是α-混合的条件下，给出了f（x）基于前礼个观测值{Xi}i=1^∞的最近邻密度估计的强相合收敛速度，当f（x）满足适当条件，收敛速度可达到0（n^-1/3（ln n）^4（1＋p）／3））．     

Precise Asymptotics in the Law of the Iterated Logarithm of Moving-Average Processes

In this paper, we discuss the moving-average process Xk = ∑i=-∞ ^∞ ai＋kεi, where {εi;-∞ 〈 i 〈 ∞} is a doubly infinite sequence of identically distributed ψ-mixing or negatively associated random variables with mean zeros and finite variances, {ai;-∞ 〈 i 〈 -∞） is an absolutely solutely summable sequence of real numbers.     

权为整数的Eisenstein空间

<正> 对上述条件3需要作些解释.对任一有理数(歧点)s,存在ρ∈SL_2(Z),使ρ(s)=i∞.上述条件3的含意是指 f(ρ~(-1)(z))j(ρ~(-1),z)~(-k)在 z=i∞的 Fourier 展开式形如sum from n=0 to ∞ a_ne(nz).即不存在 n<0的项.如果在所有歧点(包括 i∞)s,上述 Fourier 展开式中都有 a_0=0,这时 f 称为歧点型模形式.M_k(T)中所有歧点型模形式构成的子空间记作 S_k(Γ).     

一类泛函的非参数密度估计的渐近结构

设随机变量X具有分布F(00,-∞相似文献   

固定设计的时间序列半参数回归

考虑如下的半参数回归模型Yi=xTiβ+g(ti)+εi(0≤i≤n),其中{εi,0≤i≤n}和{εt,0≤t≤n}有相同的联合分布,{εt,-∞＜t＜∞}是具有零均值和有限方差σ2的严平稳α-混合时间序列.本文构造了上述模型中β,g(t)和σ2的局部多项式估计,在适当的条件下,得到了估计的渐近正态性和收敛速度.在一定的假设下,β的估计是自适应的,而且g(υ)(t)(g(t)的第υ阶导数)的估计的收敛速度是最优的.     

U-统计量的一些强极限定理的精确渐近性

设{Xn;n≥1}是一列i.i.d.随机变量序列,Un是以对称函数h(x,y)为核函数的U-统计量.记Un=2n(n-1) 1≤i相似文献   

On the weighted elliptic problems involving multi-singular potentials and multi-critical exponents

Suppose Ω belong to R^N（N≥3） is a smooth bounded domain,ξi∈Ω,0〈ai〈√μ,μ：=（（N-1）/2）^2,0≤μi〈（√μ-ai）^2,ai〈bi〈ai＋1 and pi：=2N/N-2（1＋ai-bi）are the weighted critical Hardy-Sobolev exponents, i = 1, 2,..., k, k ≥ 2. We deal with the conditions that ensure the existence of positive solutions to the multi-singular and multi-critical elliptic problem ∑i=1^k（-div（｜x-ξi｜^-2ai△↓u）-μiu/｜x-ξi｜^2（1＋ai）-u^pi-1/｜x-ξi｜^bipi）=0with Dirichlet boundary condition, which involves the weighted Hardy inequality and the weighted Hardy-Sobolev inequality. The results depend crucially on the parameters ai, bi and #i, i -- 1, 2,..., k.     

Convergence rates in the complete moment of moving-average processes

In this paper, we discuss precise asymptotics for a new kind of moment convergence of the moving-average process $X_k = \sum\limits_{i = - \infty }^\infty {a_{i + k} \varepsilon _i }$ , k ??1, where {?? _i : ??? < i < ??} is a doubly infinite sequence of independent identically distributed random variables with mean zero and the finiteness of variance, {?? _i : ??? < i < ??} is an absolutely summable sequence of real numbers, i.e., $\sum\limits_{i = - \infty }^\infty {\left| {a_i } \right| < \infty }$ .     

On moments of the maximum of partial sums of moving average processes under dependence assumptions

Let {Y i;∞ < i < ∞} be a doubly infinite sequence of identically distributed-mixing random variables and let {a i;∞ < i < ∞} be an absolutely summable sequence of real numbers.In this paper we study the moments of sup(1 ≤ r < 2,p > 0) under the conditions of some moments.     

Complete moment convergence of moving average processes under <Emphasis Type="Italic">ρ</Emphasis>-mixing assumption

Let {Y _i : ?∞ < i < ∞} be a doubly infinite sequence of identically distributed ρ-mixing random variables, and {a _i : ?∞ < i < ∞} an absolutely summable sequence of real numbers. In this paper we prove the complete moment convergence for the partial sums of moving average processes \(\{ X_n = \sum\limits_{i = - \infty }^\infty {a_i Y_{i + n,} n \geqslant 1} \} \) based on the sequence {Y _i : ?∞ < i < ∞} of ρ-mixing random variables under some suitable conditions.     

B值移动平均过程的Strassen重对数律

设 {ε,εt;t∈ Z}是 iid的 B值随机变量序列 ,{ aj;j∈ Z}是一个实数列 ,满足 ∞j=-∞|aj|<∞ .记 Xt= ∞j=-∞ajεt-j,Sn = nt=1Xt.对 p≥ 1 ,本文研究了n-1 -( p/ 2 ) (2 L2 n) -( p/ 2 ) ni=1 ‖ Si‖p 及 n-1 -( p/ 2 ) (2 L2 n) -( p/ 2 ) ni=0 ‖ Sn- Si‖ p的渐进性质 ,使得 Strassen(1 964)及 Chen(1 994)的一些结果得到推广 .     

Multiple positive solutions for semi-positone <Emphasis Type="Italic">m</Emphasis>-point boundary value problems

In this article, we establish the existence of at least two positive solutions for the semi-positone m-point boundary value problem with a parameter u (t) + λf (t, u) = 0, t ∈ (0, 1), u (0) = sum (biu (ξ i )) from i=1 to m-2, u(1)= sum (aiu(ξ i )) from i=1 to m-2, where λ > 0 is a parameter, 0 < ξ 1 < ξ 2 < ··· < ξ m 2 < 1 with 0 相似文献   

Entropy solutions of anisotropic elliptic nonlinear obstacle problem with measure data

We prove the existence of an entropy solution for a class of nonlinear anisotropic elliptic unilateral problem associated to the following equation $$\begin{aligned} -\sum _{i=1}^{N} \partial _i a_i(x,u, \nabla u) -\sum _{i=1}^{N}\partial _{i}\phi _{i}( u)=\mu , \end{aligned}$$where the right hand side $$\mu $$ belongs to $$L^{1}(\Omega )+ W^{-1, \vec {p'}}(\Omega )$$. The operator $$-\sum _{i=1}^{N} \partial _i a_i(x,u, \nabla u) $$ is a Leray–Lions anisotropic operator and $$\phi _{i} \in C^{0}({\mathbb {R}}, {\mathbb {R}})$$.     

Complete q-order moment convergence of moving average processes under φ-mixing assumptions

Let {Y _i , ?∞ < i < ∞} be a doubly infinite sequence of identically distributed φ-mixing random variables, and {a _i , ?∞ < i < ∞} an absolutely summable sequence of real numbers. We prove the complete q-order moment convergence for the partial sums of moving average processes $\left\{ {X_n = \sum\limits_{i = - \infty }^\infty {a_i + Y_{i + n} ,n \geqslant 1} } \right\}$ based on the sequence {Y _i , ?∞ < i < ∞} of φ-mixing random variables under some suitable conditions. These results generalize and complement earlier results.     

Differential properties and Fourier coefficients of functions of λ-bounded variation

пУстьλ={λ _i} _i=1 ^∞ —пОслЕ ДОВАтЕльНОсть ВЕЩЕс тВЕННых ЧИсЕл сλ _i↑∞ Иλ ^m={λ_т+ i} _i=0 ^∞ . РАссМАтРМВАУтсь 2π-пЕ РИОДИЧЕскИЕ ФУНкцИИ, Дль кОтОРых $$V_\Lambda (f) = \mathop {\sup }\limits_x \mathop {\mathop {\sup }\limits_{(a_i ,b_i ) \cap (a_j ,b_j ) = \emptyset } }\limits_{(a_i ,b_i ) \subset (x,x + 2\pi ]} \mathop \sum \limits_{\iota = 1}^\infty \frac{{\left| {f(b_i ) - f(a_i )} \right|}}{{\lambda _i }}< \infty ,$$ И Дль кОтОРых $$\mathop {\lim }\limits_{m \to \infty } V_{\Lambda ^m } (f) = 0.$$ ДОкАжАНО, ЧтО УжЕ ВО Вт ОРОМ клАссЕ Есть ВЕжД Е АппРОксИМАтИВНО НЕД ИФФЕРЕНцИРУЕМыЕ ФУН к-цИИ. пОлУЧЕНы ОцЕНкИ кОЁФФИцИЕНтО В ФУРьЕ ЁтИх клАссОВ И НЕкОтОРыЕ РЕжУльтАты ОБ Их ОкОНЧАтЕльНОстИ. кАк слЕДстВИЕ ДАНО ДОстА тОЧНОЕ УслОВИЕ Дль Их НЕсОВп АДЕНИь.