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φ-mixing     
相关语句
  φ-混合
     Let {(Xi,Yi),i ≥ 1} be a strictly stationary and φ-mixing sample sequence from (X, Y) in Rd ×r R.
     设{(Xi,Yi),i≥1}是从取值于Rd×R的总体(X,Y)中抽取的严平稳、φ-混合样本.
短句来源
     THE Hájeck-Rènyi INEQUALITY FOR φ-MIXING SEQUENCES
     φ-混合序列的Hájeck-Rènyi不等式
短句来源
     On Robust-M Detection of Random Signals inφ-Mixing Noise
     φ-混合噪声情况下随机信号的Robust-M检测
短句来源
     Empirical Likelihood Confidence Regions of Regression Coefficient in Quantile Regression Models under Φ-Mixing Samples
     Φ-混合样本下分位数回归模型回归系数的经验似然置信区域
短句来源
     Expirical Likelihood for Partially Linear Models under Φ-Mixing Error
     Φ-混合误差下部分线性模型的经验似然
短句来源
更多       
  φ-mixing
     For each n≥1, let {X_(nl), 1≤j≤k_n→∞} be strong φ-mixing, there exist an common integer M and a function φ, S_(nk)=X_(nj), 1≤k≤k_n→∞, ε>0, P{max|X_(nj)|≥ε}=0(1), as n→∞.
     对每一n≥1,{X_(nj),1≤j≤k_n→∞}为具有相同的整数M和函数φ的强φ-mixing,1≤k≤k_n→∞ε>0,当n→∞时则对某些常数A(nk),有,当且仅当,n→∞,此处,k=1,…,k_n.
短句来源
     If strong Φ-mixing sequence {X_i, i≥1} satisfy ■|X_i|=0(1).
     若强φ-mixing序列{Z_i,i≥1}有Esup■|Z_i|=0(1),n→∞,S_n为L_1-收敛,n→∞。
短句来源
     A WEAK LAW OF STRONG φ-MIXING
     强φ-Mixing的弱定理
短句来源
     TRANSFORMATION FORMULAR AND STABILITY FOR φ-MIXING
     和差变换与φ-mixing的稳定性
短句来源
     Also presented are the strong consistency and the rate of convergence of modified partitioning estimation for regression functions under some dependence samples,such as φ-mixing samples with identical distribution.
     在同分布φ-mixing相依样本下,获得了回归函数基于分割估计及改良基于分割估计的强相合性及收敛速度。
短句来源
更多       
  φ混合
     Strong Consistency of M Estimator in Linear Modelfor ρ -Mixing,φ -Mixing,ψ -Mixing Samples
     ρ混合、φ混合、ψ混合线性模型M估计的强相合性
短句来源
     For conditional t-quantiles kernel estimator of mixing sample, in this paper, we obtain its consistency rates under certain conditions. That is, for identically distributed φ-mixing samples, (X_1, Y_1), …, (X_n, Y_n)∈R~d×R~1, if? X_1 has marginal density function f;
     在一定条件下,得到了φ混合样本条件t分位数的核估计强收敛速度,即定理 对同分布的φ混合样本(X1,Y1),…,(Xn,Yn)∈Rd×R1,若 X1具有边际密度函数f;
短句来源
     Empirical likelihood estimator about parameter and distribution function is discussed under strong stationary φ-mixing dependent samples.
     在强平稳 φ混合相依样本下讨论一般参数的经验似然比估计的求法及其相应的性质 ,得到了类似独立同分布 (i.i.d.)
短句来源
     EMPIRICAL LIKELIHOOD ESTIMATOR FOR STATIONARY φ-MIXING DEPENDENT SAMPLES
     φ混合样本下的经验似然估计
短句来源
     THE STRONG LAW OF LARGE NUMBERS OF φ-MIXING PROCESS
     φ混合过程的强大数定律(英文)
短句来源
更多       
  φ-混合
     On Large Deviations for Φ-mixing Stationary Random Sequences in Hausdorff Locally Convex Topological Vector Spaces
     Hausdorff局部凸拓扑向量空间Φ-混合平稳随机序列的大偏差
短句来源
     Linear Empirical Bayes Estimation for Strongly Stationary Φ- mixing Dependent Sequence and Its Application
     强平稳Φ-混合序列下的线性经验Bayes估计及应用
短句来源
     We prove the large deviation principle fur the arithmetic means of a Φ- mixing statiunary random sequence in a Hausdorff locally convex topulugical vector space.
     证明了Hausdorff局部凸拓扑向量空间中Φ-混合平稳随机序列的算术平均的大偏差原理.
短句来源
     For the Cases of -mixing and abeolute regularity,J. Sunkloads obtained an upper bound for the bounded Lipechitz metric between the distribution functions Fn and Φ. In this peper,we extend his result to φ-mixing and ρ1 -mixing, two new mixing cases.
     J.Sunkloads在-混合和绝对正则两种情形下得到了随机变量部分和的有界LIPSCHITZ距离估计的上界.本文在φ-混合和ρ1-混合两种情形下也得到类似结果.
短句来源
     This paper structured an estimate method of excitence function s(x)=P(x>x),and studied the consictency of the estimate under {x n} ∞ 1 is stable. φ-mixing process,and s(x) is continuous.
     构造了生存函数s(x)=P(X>x)的一种估计方法^Sn(x),并在{Xn}∞1是平稳,φ-混合过程,s(x)连续的情形讨论了^Sn(x)的几种优良性质及^Sn(x)的渐近正态性.
短句来源

 

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      φ-混合
    The partial-sum processes, indexed by sets, of a stationary nonuniform φ-mixing random field on the d-dimensional integer lattice are considered.
          
    On the Central Limit Theorem for Nonuniform φ-Mixing Random Fields
          
    In this note the almost sure convergence of stationary, φ-mixing sequences of random variables according to summability methods is linked to the fulfillment of a certain integrability condition generalizing and extending the results for i.i.d.
          
    Strong Laws and Summability for φ-Mixing Sequences of Random Variables
          
    Both moving average and stationary φ-mixing type of correlated noise processes are treated.
          
    更多          
      φ-mixing
    The partial-sum processes, indexed by sets, of a stationary nonuniform φ-mixing random field on the d-dimensional integer lattice are considered.
          
    On the Central Limit Theorem for Nonuniform φ-Mixing Random Fields
          
    In this note the almost sure convergence of stationary, φ-mixing sequences of random variables according to summability methods is linked to the fulfillment of a certain integrability condition generalizing and extending the results for i.i.d.
          
    Strong Laws and Summability for φ-Mixing Sequences of Random Variables
          
    Both moving average and stationary φ-mixing type of correlated noise processes are treated.
          
    更多          
      φ混合
    The partial-sum processes, indexed by sets, of a stationary nonuniform φ-mixing random field on the d-dimensional integer lattice are considered.
          
    On the Central Limit Theorem for Nonuniform φ-Mixing Random Fields
          
    In this note the almost sure convergence of stationary, φ-mixing sequences of random variables according to summability methods is linked to the fulfillment of a certain integrability condition generalizing and extending the results for i.i.d.
          
    Strong Laws and Summability for φ-Mixing Sequences of Random Variables
          
    Both moving average and stationary φ-mixing type of correlated noise processes are treated.
          
    更多          
      φ-混合
    The partial-sum processes, indexed by sets, of a stationary nonuniform φ-mixing random field on the d-dimensional integer lattice are considered.
          
    On the Central Limit Theorem for Nonuniform φ-Mixing Random Fields
          
    In this note the almost sure convergence of stationary, φ-mixing sequences of random variables according to summability methods is linked to the fulfillment of a certain integrability condition generalizing and extending the results for i.i.d.
          
    Strong Laws and Summability for φ-Mixing Sequences of Random Variables
          
    Both moving average and stationary φ-mixing type of correlated noise processes are treated.
          
    更多          


    In this paper, some unsolved problems on conditions of the complete convergence of stationary mixing sequences {X_n} are discussed. In this way some necessary conditions and some sufficient conditions for sum from n=1 to ∞ lnn/n p(max k≤n |S_k|>εn~(1/p)<∞, (?)ε>0 and sum from n=1 to ∞ 1/n p (sup k≥n|S_k/k~(1/p)|>ε)<∞, (?)ε>0 are proved, where 0

    设{X_n}为强平稳 p-mixing或φ-mixing随机变数序列,关于{X_n}部分和的完全收敛性问题,既往的文献仅在pα>1且α>1/2的场合下,讨论过使文中(1)式成立的充要条件。本文则在pα=1且α>1/2的场合下,讨论了相应的问题,即讨论了使文中(3)、(4)成立的充分条件和使(3)式成立的必要条件问题,得到了一些结果。

    If strong Φ-mixing sequence {X_i, i≥1} satisfy ■|X_i|=0(1). n→∞. S_n∈L_1, then S_n converges almost surely.

    若强φ-mixing序列{Z_i,i≥1}有Esup■|Z_i|=0(1),n→∞,S_n为L_1-收敛,n→∞。则S_n,a.s.收敛。

    If M=1, ф(1)<1, Then Sums S_n of ф-mixing variables Satisfy ■ conver-gences in Probabilty then S_n a.s. convergences; If ф(M)<1, then ■ S_n convergences in Probability and ■ implies a.s. conver-gence.

    若M=1,ф(1)<1,则φ-mixing变量的部分和S_n成立不等式■S_n依概率收敛蕴含a.s.收敛;若ф(M)<1,有不等式■ε>0.5_n依概率收敛和■依概率收敛于0,当n→∞.蕴含a.s.收敛.

     
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