相协随机变量的指数不等式与强大数律

对相协随机变量部分和建立一些指数不等式, 这些不等式改进了Ioannides和Roussas (1999)及Oliveira (2005) 所获得的相应结论.利用这些不等式给出一些强大数律, 对协方差系数为几何递减情形,获得了强大数律的收敛速度为n^-1/2(log log n)^1/2(log n).这个收敛速度接近独立随机变量的重对数律的速度, 而且较好地改进Ioannides 和 Roussas及Oliveira分别获得的速度n^-1/3}(log n)^2/3和n^-1/3(log n)^5/3.     

U-统计量对数律的精确渐近性

设{X_n, n ≥1}是独立同分布随机变量序列, U_n 是以对称函数(x, y) 为核函数的U -统计量. 记U_n =2/n(n-1)∑_{1≤i h(Xi, Xj), h1(x) =Eh(x, X2). 在一定条件下, 建立了∑n=2^∞(logn)^δ-1EUn²I {I U n |≥n ^1/2√lognε}及∑n=3^∞(loglognε)^δ-1/logn EUn² I {|U n|≥n^1/2√log lognε} 的精确收敛速度.}     

随机删失半参数回归模型中估计的渐近性质

设Y是表示生存时间并遵从下面半参数模型Y=Xβ+g(T)+ε的随机变量,(X,T)是取值于R×[0,1]上的随机变量,β是未知参数,g(·)是[0,1]上的未知回归函数,ε是随机误差。当Y因受某种随机干扰而被随机右删失时,就删失分布未知的情形分别定义了β与g(·)的估计^{^}β_n与^{^}g_n(·),在一定条件下证明了^{^}β_n的渐近正态性,并得到了^{^}g_n(·)的最优收敛速度。     

关于Szeg?的一个不等式

设P_n(x)为[0,∞)上次数不超过n的代数多项式,则有‖p′_n(x)e^-x‖_[0,∞)≤(6.3n+1)‖p_n(x)e^-x‖_[0,∞).若p_n(x)同时又是奇函数或偶函数,则有‖p′_n(x)e^-x‖_[0,∞)≤(1.8+7n^1/2)‖p相似文献   

切于已知球的单形宽度

Let w(△_n) denote the width of a non-degenerate simplex △_n in Eⁿ and r(△_n) denote the inradius of the simplex.Then, in this paper, we prove the ine-qunlity as below: Theorem:w(△_n)≤β_nr(△_n) where β_n =(n^1/2(n+1))/([(n+1)/2]^1/2(n+1-[(n+1)/2])^1/2) The equality holds if and only if the simplex is regular.     

B-值随机变量序列叠对数律的收敛速度

设{X,X_n;n≥1}是在可分Banach空间(B,‖·‖)中取值的独立同分布随机变量序列,并且EX=0,Ef²(X)<+∞,f∈B^*,记S_n=X₁+…+X_n,n≥1.本文的目的是在适当的充要条件下研究和的收敛速度.作为本文结果的应用,分别给出了X满足有界叠对数律和紧叠对数律各一个新的充要条件;同时,本文改进了文献[3]和[4]在实空间情形所建立的一些结果.     

U-统计量的分布的非一致性收敛速度

Callaert和Janssen在只假定核的三阶矩有限的条件下,得到了U-统计量的分布的最佳一致性收敛速度O(n^-1/2)。本文在同样条件下,得到了理想的非一致性收敛速度O(n^-1/2(1+|x|)^-3)。     

NA随机场对数律的收敛速度

设d是一个正整数, N ^d是d -维正整数格点.设{X_n , n∈N ^d} 是一同分布的负相伴随机场, 记S_n =∑_{k≤ n} X_k, S_n^(k)=S_n-X_k, 如果r >2, EX₁ = 0 和σ²= Var(X₁}, 则存在一个正数M:=100√(r-2)(1+σ²)使得下列条件等价 (I)E |X₁|^r (log|X₁|)^d-1-r/2 <∞; (II)∑_{n∈ N^d} |n|^r/2-2P(max_{1≤ k≤ n} |S_n^(k)|≥ (2^d+1 )ε√|n| log |n |) <∞,∨ε > M; (III)∑_{n∈N ^d} |n|^r/2-2P(max_{1≤ k≤n} |S_k |≥ε√| n} log| n |) <∞,∨ε > M. (III)\ \ $\sum\limits_{{{\bf n}}\in {{\cal N}}^{d}} |n|^{r/2-2} P(\max\limits_{{\bf 1}\leq{\bf k}\leq{\bf n}}|S_{{\bf k}}|\geq \varepsilon \sqrt{|{\bf n}|\log |{\bf n}|})<\infty$, $\forall\varepsilon>M$.     

用Hermite-Fejér型插值多项式逼近连续函数

Let f(x)∈C_[-1,1],T_n(x)=cos (n arccos x),U_n(x)=(sin((n+1)arccosx))/(1-x²)^1/2,P_n(x) be the Legendre polynomials of degree n. And let ω(t ) be a given modulus of continuity, H_ω={f|ω(f,t)≤ω(t)}.A. K. Sharma and J. Tzimbalario(J. Appro. Th., 13(1975), 431-442) considered the operators L_n,p (f, x) (p= 0, 1, 2,3) and obtained some theorems.In this paper, we prove the following theorems.     

右半平面内解析函数的准确零(R)级

Let f(s)=(?)a_ne^-λ_m3(s=σ+it),0<λ_n↑+∞), where (?)(n/logU(λ_n))=E<+∞,(?)(log|α_n|/λ_n)=0.     

Exponential Inequalities and Complete Convergence for Extended Negatively Dependent Random Variables

Some exponential inequalities and complete convergence are established for extended negatively dependent（END） random variables. The inequalities extend and improve the results of Kim and Kim（On the exponential inequality for negative dependent sequence. Communications of the Korean Mathematical Society, 2007, 22（2）： 315-321） and Nooghabi and Azarnoosh（Exponential inequality for negatively associated random variables. Statisti- cal Papers, 2009, 50 （2）： 419-428）. We also obtain the convergence rate O（n-1/2 In1/2 n） for the strong law of large numbers, which improves the corresponding ones of Kim and Kim, and Nooghabi and Azarnoosh.     

Exponential inequalities for associated random variables and strong laws of large numbers

Some exponential inequalities for partial sums of associated random variables are established. These inequalities improve the corresponding results obtained by Ioannides and Roussas (1999), and Oliveira (2005). As application, some strong laws of large numbers are given. For the case of geometrically decreasing covariances, we obtain the rate of convergence n-1/2(log log n)1/2(logn) which is close to the optimal achievable convergence rate for independent random variables under an iterated logarithm, while Ioannides and Roussas (1999), and Oliveira (2005) only got n-1/3(logn)2/3 and n-1/3(logn)5/3, separately.     

Some Exponential Inequalities for Positively Associated Random Variables and Rates of Convergence of the Strong Law of Large Numbers

We present some exponential inequalities for positively associated unbounded random variables. By these inequalities, we obtain the rate of convergence n ^−1/2 β _n log ^3/2 n in which β _n can be particularly taken as (log log n)^1/σ with any σ>2 for the case of geometrically decreasing covariances, which is faster than the corresponding one n ^−1/2(log log n)^1/2log ² n obtained by Xing, Yang, and Liu in J. Inequal. Appl., doi: (2008) for the case mentioned above, and derive the convergence rate n ^−1/2 β _n log ^1/2 n for the above β _n under the given covariance function, which improves the relevant one n ^−1/2(log log n)^1/2log n obtained by Yang and Chen in Sci. China, Ser. A 49(1), 78–85 (2006) for associated uniformly bounded random variables. In addition, some moment inequalities are given to prove the main results, which extend and improve some known results.     

Expose-and-merge exploration and the chromatic number of a random graph

The expose-and-merge paradigm for exploring random graphs is presented. An algorithm of complexityn ^O(logn) is described and used to show that the chromatic number of a random graph for any edge probability 0<p<1 falls in the interval $$\left[ {\left( {\frac{1}{2} - \varepsilon } \right)\log (1/(1 - p))\frac{n}{{\log n}}, \left( {\frac{2}{3} + \varepsilon } \right)\log (1/(1 - p))\frac{n}{{\log n}}} \right]$$ with probability approaching unity asn→∞.     

Limit theorems for the ratio of the Kaplan-Meier estimator or the Altshuler estimator to the true survival function

LetX ₁,X ₂, ...,X _n be a sequence of nonnegative independent random variables with a common continuous distribution functionF. LetY ₁,Y ₂, ...,Y _n be another sequence of nonnegative independent random variables with a common continuous distribution functionG, also independent of {X _i }. We can only observeZ _i =min(X _i ,Y _i ), and . LetH=1−(1−F)(1−G) be the distribution function ofZ. In this paper, the limit theorems for the ratio of the Kaplan-Meier estimator or the Altshuler estimator to the true survival functionS(t) are given. It is shown that (1)P(δ_(n)=1 i.o.)=0 ifF(τ _H ) < 1 andP(δ _n =0 i.o. )=0 ifG(τH) > 1 where δ_(n) is the corresponding indicator function of and have the same order a.s., where {T _n } is a sequence of constants such that 1−H(T _n )=n ^−α(logn)^β(log logn)^γ.     

How quadratic are the natural numbers?

Abstract. For natural numbers n we inspect all factorizations n = ab of n with a ￡ ba \le b in \Bbb N\Bbb N and denote by n=a_n b_nn=a_n b_n the most quadratic one, i.e. such that b_n - a_nb_n - a_n is minimal. Then the quotient k(n) : = a_n/b_n\kappa (n) := a_n/b_n is a measure for the quadraticity of n. The best general estimate for k(n)\kappa (n) is of course very poor: 1/n ￡ k(n) ￡ 11/n \le \kappa (n)\le 1. But a Theorem of Hall and Tenenbaum [1, p. 29], implies(logn)^-d-e ￡ k(n) ￡ (logn)^-d(\log n)^{-\delta -\varepsilon } \le \kappa (n) \le (\log n)^{-\delta } on average, with d = 1 - (1+log₂  2)/log2=0,08607 ?\delta = 1 - (1+\log _2 \,2)/\log 2=0,08607 \ldots and for every e > 0\varepsilon >0. Hence the natural numbers are fairly quadratic.¶k(n)\kappa (n) characterizes a specific optimal factorization of n. A quadraticity measure, which is more global with respect to the prime factorization of n, is k^*(n): = ?_{1 ￡ a ￡ b, ab=n} a/b\kappa ^*(n):= \textstyle\sum\limits \limits _{1\le a \le b, ab=n} a/b. We show k^*(n) ~ \frac 12\kappa ^*(n) \sim \frac {1}{2} on average, and k^*(n)=W(2^{\frac 12(1-e) log n/log ₂n})\kappa ^*(n)=\Omega (2^{\frac {1}{2}(1-\varepsilon ) {\log}\, n/{\log} _2n})for every e > 0\varepsilon>0.     

The complexity and depth of Boolean circuits for multiplication and inversion in some fields <Emphasis Type="Italic">GF</Emphasis>(2<Superscript><Emphasis Type="Italic">n</Emphasis></Superscript>)

Let n = (p − 1) · p ^k , where p is a prime number such that 2 is a primitive root modulo p, and 2 ^p−1 − 1 is not a multiple of p ². For a standard basis of the field GF(2 ⁿ ), a multiplier of complexity O(log log p)n log n log log _p n and an inverter of complexity O(log p log log p)n log n log log _p n are constructed. In particular, in the case p = 3 the upper bound

An iterated logarithm law related to decimal and continued fraction expansions

For an irrational number x and n ≥ 1, we denote by k _n (x) the exact number of partial quotients in the continued fraction expansion of x given by the first n decimals of x. G. Lochs proved that for almost all x, with respect to the Lebesgue measure In this paper, we prove that an iterated logarithm law for {k _n (x): n ≥ 1}, more precisely, for almost all x, for some constant σ > 0. Author’s address: Department of Mathematics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P.R. China