关于运营商滥用市场优势地位行为的思考

我国对移动通信网络建设的严格控制、网络的外部性特征、信息资源的不对称、电信监管力量薄弱等因素使得移动运营商得以滥用市场优势地位获得高额利润, 这在一定程度上阻碍我国移动增值业务的进一步发展.正确认识和处理移动运营商与服务提供商之间的关系,适当分离运营商的基础话音业务和自营增值业务,充分发挥行业协会的作用, 制定<反垄断法>实施细则,尽快出台<电信法>等将有助于防止移动运营商滥用市场优势地位.     

Adaptive Local Polynomial Whittle Estimation of Long‐range Dependence

The local Whittle (or Gaussian semiparametric) estimator of long range dependence, proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of convergence and a finite sample bias that can be large. In this paper, we generalize the local Whittle estimator to circumvent these problems. Instead of approximating the short‐run component of the spectrum, ϕ(λ) , by a constant in a shrinking neighborhood of frequency zero, we approximate its logarithm by a polynomial. This leads to a “local polynomial Whittle” (LPW) estimator. We specify a data‐dependent adaptive procedure that adjusts the degree of the polynomial to the smoothness of ϕ(λ) at zero and selects the bandwidth. The resulting “adaptive LPW” estimator is shown to achieve the optimal rate of convergence, which depends on the smoothness of ϕ(λ) at zero, up to a logarithmic factor.     

大数据背景下互联网平台反垄断法适用难题及对策研究

当前正是数据经济和平台经济快速发展时期,在两者深度融合促进市场蓬勃发展的同时,也为反垄断法在规制垄断协议、界定相关市场、审核经营者集中申报方面带来一些难题。为此,需落脚大数据本身,以互联网平台双边市场特征为出发点,引入算法规范价值伦理、市场调节和调研机制来尝试规制互联网平台垄断协议。当界定互联网平台相关市场时,应厘清涉案平台类型,定位被诉损害行为发生市场,选择适合的界定方法。在合理情况下,探寻淡化“相关市场”概念。需建立多元申报标准,在审查时注意找出经营者集中的背后动因,在一定情况下将商谈作为审查的必经程序,以此规避以扼杀创新和限制竞争为目的的经营者集中。     

Regression analysis of informative current status data with the semiparametric linear transformation model

Many methods have been developed in the literature for regression analysis of current status data with noninformative censoring and also some approaches have been proposed for semiparametric regression analysis of current status data with informative censoring. However, the existing approaches for the latter situation are mainly on specific models such as the proportional hazards model and the additive hazard model. Corresponding to this, in this paper, we consider a general class of semiparametric linear transformation models and develop a sieve maximum likelihood estimation approach for the inference. In the method, the copula model is employed to describe the informative censoring or relationship between the failure time of interest and the censoring time, and Bernstein polynomials are used to approximate the nonparametric functions involved. The asymptotic consistency and normality of the proposed estimators are established, and an extensive simulation study is conducted and indicates that the proposed approach works well for practical situations. In addition, an illustrative example is provided.     

New aspects of Bregman divergence in regression and classification with parametric and nonparametric estimation

In statistical learning, regression and classification concern different types of the output variables, and the predictive accuracy is quantified by different loss functions. This article explores new aspects of Bregman divergence (BD), a notion which unifies nearly all of the commonly used loss functions in regression and classification. The authors investigate the duality between BD and its generating function. They further establish, under the framework of BD, asymptotic consistency and normality of parametric and nonparametric regression estimators, derive the lower bound of their asymptotic covariance matrices, and demonstrate the role that parametric and nonparametric regression estimation play in the performance of classification procedures and related machine learning techniques. These theoretical results and new numerical evidence show that the choice of loss function affects estimation procedures, whereas has an asymptotically relatively negligible impact on classification performance. Applications of BD to statistical model building and selection with non‐Gaussian responses are also illustrated. The Canadian Journal of Statistics 37: 119‐139; 2009 © 2009 Statistical Society of Canada     

Non parametric hypothesis tests for comparing reliability functions

In reliability and related disciplines, comparing reliability functions of two (or more) aging processes is a crucial step in the process of determining reliability and understanding an aging process. The aim of this paper is to propose a non parametric statistical methodology to compare two populations based on their mean residual life function and expected inactivity time function. We introduce some novel hypothesis testing procedures that involve both Cramér–von Mises- and Kolmogorov–Smirnov-type test statistics and their decision rules are constructed based on the asymptotic distributions of these test statistics and bootstrapping method. We study the practical behavior of the proposed testing procedures extensively through simulations. The results reveal that the proposed hypothesis testing procedures perform efficiently in identifying small and large differences. Two real-life examples are discussed to demonstrate the practical utility of the tests.     

Theoretical L-moments and TL-moments using combinatorial identities and finite operators

Moments have been traditionally used to characterize a probability distribution. Recently, linear moments (L-moments) and trimmed L-moments (TL-moments) are appealing alternatives to the conventional moments. This paper focuses on the computation of theoretical L-moments and TL-moments and emphasizes the use of combinatorial identities. We are able to derive new closed-form formulas of L-moments and TL-moments for continuous probability distributions. Finally, closed-form formulas for the L-moments for the exponential distribution and the uniform distribution are also obtained.     

Iterated Partial Sum Sequences of Regression Residuals and Tests for Changepoints with Continuity Constraints

Iterated partial sum sequences of regression least squares residuals are defined and large sample properties of sequences of stochastic processes defined by these iterated partial sums are discussed. Also, finite sample properties of the iterated partial sum sequences are obtained. These include a property of least squares residuals of polynomial fits to equispaced data, namely the iterated partial sums sum to 0 provided that the order of iteration is not greater than the order of the polynomial, thus extending the well-known result that residuals sum to 0. Iterated partial sums are shown to play an important role in testing regression parameters for changes at unknown times under the constraint of continuity.     

关于多元指数型算子的一致逼近(Ⅱ)

设L_(n,m) (F (u,v);x,y)是二元指数型算子,在本文中,我们借助于K-泛函,讨论了当0相似文献   

正交多项式回归模型参数估计的格子设计及其最小二乘估计

对二元二次多项式回归模型进行预先正交化处理，提出使用因子空间的N等份的格子设计的观点，推导出了信息矩阵的一般性结构，并给出了该设计的非退化条件及其最小二乘估计和对应的协方差矩阵。