出版媒介的融合方式及其发展

我国出版媒介的融合,大致有出版媒介自身的融合、出版媒介与其他媒介的融合、出版媒介与非媒介行业的融合等形式,每种形式又有不同的分支。我国出版媒介在跨地区、跨媒体、跨所有制、跨行业等方面的融合均已有一定发展,但某些环节还比较薄弱,需要加强,一些关系还待理顺。随着政策的进一步放开,出版媒介组织机构问的融合将以自愿、自主发展为主。媒介形态的融合将进一步加大,资本在媒介融合中的纽带作用将更加明显,出版媒介融合的多元化趋势将极大地促进出版产业的完善和发展。     

融合文化本质与受众自我赋权

融合文化本质上是一种参与式和互动式文化。在传播新技术的驱动下,受众通过参与和互动以生产融合文化,并与＂传者生产＂进行博弈而实现了自我赋权,最终分享了原来由垄断媒介文本和媒介文化生产的＂传者＂所牢牢掌控的媒介文化权力。融合文化还是一种新型的大众文化,也是现阶段正在出现的新兴文化样式和文化特征。当前,融合文化中受众的自我赋权及其赋权模式不断扩张和深入发展,但却面临着复杂的现实困境。     

A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter

In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^d_r, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^d_r, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^d_r. These results show that the bias of ^d_r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^d_r attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.     

The Singularity of the Information Matrix of the Mixed Proportional Hazard Model

This paper presents new identification conditions for the mixed proportional hazard model. In particular, the baseline hazard is assumed to be bounded away from 0 and ∞ near t = 0. These conditions ensure that the information matrix is nonsingular. The paper also presents an estimator for the mixed proportional hazard model that converges at rate N^−1/2.     

Estimation of a Conditional Copula and Association Measures

Abstarct. This paper is concerned with studying the dependence structure between two random variables Y ₁ and Y ₂ conditionally upon a covariate X. The dependence structure is modelled via a copula function, which depends on the given value of the covariate in a general way. Gijbels et al. (Comput. Statist. Data Anal., 55, 2011, 1919) suggested two non‐parametric estimators of the ‘conditional’ copula and investigated their numerical performances. In this paper we establish the asymptotic properties of the proposed estimators as well as conditional association measures derived from them. Practical recommendations for their use are then discussed.     

Asymptotically optimal Berry-Esseen-type bounds for distributions with an absolutely continuous part

Recursive and closed form upper bounds are offered for the Kolmogorov and the total variation distance between the standard normal distribution and the distribution of a standardized sum of n independent and identically distributed random variables. The method employed is a modification of the method of compositions along with Zolotarev's ideal metric. The approximation error in the CLT obtained vanishes at a rate O(n^−k/2+1), provided that the common distribution of the summands possesses an absolutely continuous part, and shares the same k−1 (k?3) first moments with the standard normal distribution. Moreover, for the first time, these new uniform Berry-Esseen-type bounds are asymptotically optimal, that is, the ratio of the true distance to the respective bound converges to unity for a large class of distributions of the summands. Thus, apart from the correct rate, the proposed error estimates incorporate an optimal asymptotic constant (factor). Finally, three illustrative examples are presented along with numerical comparisons revealing that the new bounds are sharp enough even to be used in practical statistical applications.     

国内地区间价格水平差异收敛性再检验

由于以CPI与RPI构建的地区间相对价格水平均存在较严重的截面相关性,而类似文献所采用的第一代检验方法无法克服这一问题,故利用第二代检验方法对国内地区间相对价格水平差异的收敛性做了重新检验。结果表明：以CPI构建的地区间相对价格水平在本研究的大多数时间段内均不收敛,而以RPI构建的价格水平仅在部分时间段内趋于收敛,这与类似文献基于第一代检验方法得出的乐观结论形成了鲜明对比。按照地区特征对样本地区进行分组研究,发现相对价格水平倾向于在国内较富裕以及较开放的地区间收敛,而研究结果表明经济增长和通胀水平对地区间价格水平差异收敛性的影响并不确定。     

通信企业"三网融合"方案设计研究

随着经济和技术的发展,传统的业务服务已经不能满足人们的需求,"三网融合"已经成为网络业务发展的必然趋势.通过对"三网融合"国内外现状的研究,分析了当今"三网融合"面临的问题,结合通信企业的实际情况,提出采用分布式流媒体技术进行通信企业"三网融合"方案设计,并针对不同规模通信企业,提出了紧凑型组网、城域网本地组网、多级分布式组网三种组网方案.该"三网融合"设计方案可以有效地节省骨干网带宽、保证QoS,提高用户满意度,对各级通信企业搭建多媒体数据中心具有一定推广作用.     

On Complete Convergence for an Extended Negatively Dependent Sequence

In this article, the Rosenthal-type maximal inequality for extended negatively dependent (END) sequence is provided. By using the Rosenthal type inequality, we present some results of complete convergence for weighted sums of END random variables under mild conditions.     

Statistical Analysis of Parameter Estimation for 2-D Harmonics in Multiplicative and Additive Noise

This article considers the problem of parameter estimation for two dimensional (2-D) multi-component harmonics in non zero-mean multiplicative and additive noise. The least squares estimators (LSEs) are proposed to estimate the coherent model parameters, and some statistical results of the LSEs are obtained, including strong consistency, strong convergence rate, and asymptotic normality. Furthermore, the LSEs-based estimators are proposed to estimate the noncoherent model parameters, and the strong consistency and the asymptotic normality are also proved. Finally, some numerical experiments are performed to see how the asymptotic results work for finite sample sizes.