网络服务提供者著作权侵权中的双重注意义务

《民法典》侵权责任编对原有通知删除规则进行了科学修正，但事前保护缺位与事后救济程序失范的问题仍然存在。随着网络服务提供者完成角色转型和技术升级，其作为网络侵权风险的控制者和参与者，有必要且有能力承担未通知阶段的主动预防义务和已通知阶段的证明材料审查义务，以弥补著作权保护和用户利益保护的漏洞。双重注意义务应分别与网络服务提供者对侵权危险的预期和控制能力以及材料审查能力相适应。未通知阶段之注意义务以技术措施为主要履行方式，其注意标准的认定应综合考量技术水平、服务类型、内容介入程度、是否直接获取收益等要素，未尽该注意义务仅为过错认定的考量因素而非唯一标准，并不必然导致侵权责任。已通知阶段之注意义务仅限于对提交的证明材料进行形式审查和有限的实质审查，尽到此注意义务的，可以免于承担侵权责任。     

Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

巴渝古崖居的空间分布与景观特征

巴渝古崖居的分布与地理、地质、交通等诸多因素有关，以成渝交通要道、长江干流和支流为线，串起沿途各个点，由线成面，呈现出渝西、渝东北两头集中、整体北多南少的分布特征。巴渝古崖居大多开凿于明清晚期，这一时期巴渝许多地区战乱频繁、匪患猖獗。古崖居的集中分布与这些地区相吻合，从侧面印证了巴渝古崖居的空间分布特征。巴渝古崖居的广泛开凿体现了古人高超的建筑艺术以及社会历史文化的变迁。     

A new generalized Weibull distribution in income economic inequality curves

Researchers have been developing various extensions and modified forms of the Weibull distribution to enhance its capability for modeling and fitting different data sets. In this note, we investigate the potential usefulness of the new modification to the standard Weibull distribution called odd Weibull distribution in income economic inequality studies. Some mathematical and statistical properties of this model are proposed. We obtain explicit expressions for the first incomplete moment, quantile function, Lorenz and Zenga curves and related inequality indices. In addition to the well-known stochastic order based on Lorenz curve, the stochastic order based on Zenga curve is considered. Since the new generalized Weibull distribution seems to be suitable to model wealth, financial, actuarial and especially income distributions, these findings are fundamental in the understanding of how parameter values are related to inequality. Also, the estimation of parameters by maximum likelihood and moment methods is discussed. Finally, this distribution has been fitted to United States and Austrian income data sets and has been found to fit remarkably well in compare with the other widely used income models.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

Changes in work and care trajectories during the transition to motherhood

In most mid- and high-income countries, there have been significant demographic, structural, and cultural changes in the past decades. However, we know little about how these changes have shaped women's work patterns during a key life stage: the transition to motherhood. Using longitudinal data from Chile, covering over 30 years of employment histories and three periods of first births (1980–2010), I conduct sequence analysis to identify women's work-care trajectories during an eight-year period of the transition to motherhood. Over time, I find that continuous care work at home has declined, for which education plays a key role, while the chances of working continuously have not changed over time. Instead, I find an increasing trend of unsteady paths that combine paid work with either caretaking or unemployment. I discuss how these changes, as well as their association with education, have important implications for both gender and social inequality.     

Confidence intervals,significance values,maximum likelihood estimates,etc. sharpened into Occam’s razors

Abstract

Confidence sets, p values, maximum likelihood estimates, and other results of non-Bayesian statistical methods may be adjusted to favor sampling distributions that are simple compared to others in the parametric family. The adjustments are derived from a prior likelihood function previously used to adjust posterior distributions.     

On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

Analyzing multiple vector autoregressions through matrix-variate normal distribution with two covariance matrices

Abstract

This article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method.