Moderate Deviations for Bayes Posteriors

Let ( X_k ) k be a sequence of i.i.d. random variables taking values in a set , and consider the problem of estimating the law of X₁ in a Bayesian framework. We prove, under mild conditions on the prior, that the sequence of posterior distributions satisfies a moderate deviation principle.     

A Review of Kyoto Protocol Adoption in Russia: Joint Implementation in Focus

Russia’s role in ‘animation’ of the Kyoto Protocol was crucial. Its initial vacillation on ratification was predominantly due to political bargaining with the EU. Domestic economic rationales [i.e. impacts of emission trading and Joint Implementation (JI) projects] were important to a much lesser extent and environmental motives did not seem to play any role in the decision. Since the Protocol entered into force, there have been significant delays in complete establishment of policy implementation frameworks, which are necessary for Russia to start benefiting from JI and emission trading. Only recently, in 2007, have GHG inventories and a national registry been established and the responsibilities for implementation of the Protocol and JI among the government departments have been distributed only to a certain extent. Some constraints hindering JI projects, such as vague legislation, an unfavourable economic climate, lack of commitment to JI projects, corruption, xenophobia, state and agency ‘capture’ still remain.      

Infill asymptotics for adaptive kernel estimators of spatial intensity

We apply the Abramson principle to define adaptive kernel estimators for the intensity function of a spatial point process. We derive asymptotic expansions for the bias and variance under the regime that n independent copies of a simple point process in Euclidean space are superposed. The method is illustrated by means of a simple example and applied to tornado data.     

Sequential estimation problems for negative exponential populations

The literature on sequential estimation problems for negative exponential populations has been reviewed here, We attempt to bring in all the published and unpublished materials known to us in a fairly coherent fashion. Both the concepts and theoretical findings are discussed.     

On Bartlett correction of empirical likelihood for regularly spaced spatial data

Bartlett correction constitutes one of the attractive features of empirical likelihood because it enables the construction of confidence regions for parameters with improved coverage probabilities. We study the Bartlett correction of spatial frequency domain empirical likelihood (SFDEL) based on general spectral estimating functions for regularly spaced spatial data. This general formulation can be applied to testing and estimation problems in spatial analysis, for example testing covariance isotropy, testing covariance separability as well as estimating the parameters of spatial covariance models. We show that the SFDEL is Bartlett correctable. In particular, the improvement in coverage accuracies of the Bartlett‐corrected confidence regions depends on the underlying spatial structures. The Canadian Journal of Statistics 47: 455–472; 2019 © 2019 Statistical Society of Canada     

Kernel naive Bayes discrimination for high‐dimensional pattern recognition

Kernel discriminant analysis translates the original classification problem into feature space and solves the problem with dimension and sample size interchanged. In high‐dimension low sample size (HDLSS) settings, this reduces the ‘dimension’ to that of the sample size. For HDLSS two‐class problems we modify Mika's kernel Fisher discriminant function which – in general – remains ill‐posed even in a kernel setting; see Mika et al. (1999). We propose a kernel naive Bayes discriminant function and its smoothed version, using first‐ and second‐degree polynomial kernels. For fixed sample size and increasing dimension, we present asymptotic expressions for the kernel discriminant functions, discriminant directions and for the error probability of our kernel discriminant functions. The theoretical calculations are complemented by simulations which show the convergence of the estimators to the population quantities as the dimension grows. We illustrate the performance of the new discriminant rules, which are easy to implement, on real HDLSS data. For such data, our results clearly demonstrate the superior performance of the new discriminant rules, and especially their smoothed versions, over Mika's kernel Fisher version, and typically also over the commonly used naive Bayes discriminant rule.     

行业特色高校学科发展模式:美国一流大学的启示

特色学科是差异化战略的具体体现,是行业特色高校核心竞争力的核心要素和集中体现。在美国保持特色优势是行业特色高校的立校之本,其学科发展有均衡发展与重点突破,有限发展与综合发展,学科交叉、协同发展几种典型模式。就我国而言多学科交叉协同、非均衡发展模式是行业特色高校的强校之路。成都理工大学“恃优先行,以点带面;以优促精,全面提高”的学科发展模式正是国内行业特色高校发展的典型案例。     

建筑物区分所有权及专有权的概念辨析

建筑物区分所有权制度是近现代社会发展起来的一项新型不动产所有权制度。专有所有权是业主对其建筑物专有部分享有的专有、使用、收益和处分的权利,其性质为对空间的所有权。     

Does Joint Physical Custody “Cause” Children’s Better Outcomes?

ABSTRACT

Policymakers and researchers are concerned with whether joint physical custody (JPC) produces better outcomes for children than sole custody. Although several review articles summarizing up to 61 empirical articles demonstrate very positive answers, many of the research designs used compromise the ability to claim that it is JPC per se—and not selection effects—that causes the effect. We discuss several research design issues, such as propensity score analysis, that can more powerfully probe the question of causality. Some studies have already been conducted employing these strategies and more are recommended and likely to soon be forthcoming. On the basis of this comprehensive review we conclude that JPC probably does cause benefits to children on average, and that social scientists can now provisionally recommend rebuttably presumptive JPC to policymakers.