局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

Resampling-based stepwise multiple testing procedures with applications to clinical trial data

Endpoints in clinical trials are often highly correlated. However, the commonly used multiple testing procedures in clinical trials either do not take into consideration the correlations among test statistics or can only exploit known correlations. Westfall and Young constructed a resampling-based stepdown method that implicitly utilizes the correlation structure of test statistics in situations with unknown correlations. However, their method requires a “subset pivotality” assumption. Romano and Wolf proposed a more general stepdown method, which does not require such an assumption. There is at present little experience with the application of such methods in analyzing clinical trial data. We advocate the application of resampling-based multiple testing procedures to clinical trials data when appropriate. We have conjectured that the resampling-based stepdown methods can be extended to a stepup procedure under appropriate assumptions and examined the performance of both stepdown and stepup methods under a variety of correlation structures and distribution types. Results from our simulation studies support the use of the resampling-based methods under various scenarios, including binary data and small samples, with strong control of Family wise type I error rate (FWER). Under positive dependence and for binary data even under independence, the resampling-based methods are more powerful than the Holm and Hochberg methods. Last, we illustrate the advantage of the resampling-based stepwise methods with two clinical trial data examples: a cardiovascular outcome trial and an oncology trial.     

大数据背景下基于社交网络的聚类随机游走抽样算法研究

数字经济时代,社交网络作为数字化平台经济的重要载体,受到了国内外学者的广泛关注。大数据背景下,社交网络的商业应用价值巨大,但由于其网络规模空前庞大,传统的网络分析方法 因计算成本过高而不再适用。而通过网络抽样算法获取样本网络,再推断整体网络,可节约计算资源, 因此抽样算法的好坏将直接影响社交网络分析结论的准确性。现有社交网络抽样算法存在忽略网络内部拓扑结构、容易陷入局部网络、抽样效率过低等缺陷。为了弥补现有社交网络抽样算法的缺陷,本文结合大数据社交网络的社区特征,提出了一种聚类随机游走抽样算法。该方法首先使用社区聚类算法将原始网络节点进行社区划分,得到多个社区网络,然后分别对每个社区进行随机游走抽样获取样本网 络。数值模拟和案例应用的结果均表明,聚类随机游走抽样算法克服了传统网络抽样算法的缺点,能够在降低网络规模的同时较好地保留原始网络的结构特征。此外,该抽样算法还可以并行运算,有效提升抽样效率,对于大数据背景下大规模社交网络的抽样实践具有重大现实意义。     

Perimeter-area ratio effects of urbanization intensity on forest characteristics,landscape patterns and their associations in Harbin City,Northeast China

To maximize the ecological services of urban forests, a better understanding of the effects of urbanization on urban forest characteristics, landscape metrics, and their associations is needed for landscape-related regulations in space-limited green infrastructure of metropolitan regions. In this study, Harbin, a typical fast-growing provincial-capital city in Northeast China, is used as a case study. Based on remote sensing images, field surveys, and correlation and variation partitioning analyses, we conclude that landscape characteristics and forest attributes have large variations among different urbanization intensity (UI) regions. Forest patch density (PD), landscape shape index, woody plants species richness, and the Shannon–Wiener index (H′) increased linearly, while stem section area and tree height decreased linearly with the increasing of UIs. UI had a greater influence on tree size and forest community attributes than the forest landscape pattern. Accordingly, any landscape regulation on forest attributes should be implemented according to UIs. In addition, Euclidean nearest neighbor distance(ENN-MN), mean perimeter-area ratio (PARA-MN), fractal dimension index(FRAC-MN), and PD could probably indicate forest attributes the most, e.g., the increase of PARA-MN may be accompanied with taller trees in low and heavy UI regions, but lower woody plants species evenness in low and medium UI regions. More diversified woody plants species, and afforested areas should be advocated in a low UI region, while in a heavy UI region, the conservation of large trees should be implemented. Our results highlight that the implementation of urban forest management should vary according to different urbanization regions to maximize ecological services.

     

论民族生境与民族文化建构

民族学经过一个多世纪的探索，逐步地达成了一个共识，建构一种文化并不是一件轻而易举的事情。文化是指导人类生存发展延续的信息系统，文化的建构是以所处自然生态系统为底本，以并存的社会生态系统为参照，文化这一信息系统不断偏离与回归所处自然生态系统与社会生态系统，在世代延续过程中逐步认知、积累其成败的经验与教训，并在传承的过程中不断地完善和丰富起来。民族以文化为分野，不同民族所处自然环境与社会环境互有差异，这就形成了民族生境的差异性，而民族生境的差异性也同样会建构出不同民族文化事实体系的差异性来。     

机器学习视角下中国去产能产业的识别

随着中国环境压力的增加,政府提出了供给侧改革,去产能是改革的主要内容,但是由于产业特征的实时演变,需要对政策进行完善。文章运用模糊C均值算法和支持向量机算法分析现阶段需要进行去产能的产业,结果发现在现行去产能政策中大部分行业是需要去产能的,但煤炭开采和洗选业以及铁路、船舶、航空航天和其他运输设备制造业已不适合继续去产能,同时将化学原料和化学制品制造业加入去产能行列中。     

Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

结构分量模型选择与稳健性研究

本文的主要工作是对季节调整中结构分量模型的选择及稳健性问题进行研究。通过构造备选模型、引入正态先验分布及对MCMC抽样方案进行重新设计,本文提出了能同时有效地辨别出分量个数和分量随机性与否的模型选择方法。将该方法应用于对中国季度GDP序列的季节调整建模分析中。分析结果显示,本文所提出的模型选择方法具有较高的筛选能力,并且对先验分布超参数值的变动也具有很好的稳健性。     

磷酸酯/Fe3+ 型油基冻胶压裂液性能研究

针对磷酸酯/Al3+ 交联的油基压裂液交联速度慢，交联剂溶解性慢、稳定性差和价格高等缺点，首次对磷酸酯/Fe3+ 交联的油基压裂液体系进行了研究。通过对铁交联剂体系的优化，筛选一种磷酸酯/Fe3+ 交联的新型交联剂体系，并对磷酸酯/Fe3+ 油基冻胶压裂液性能进行了评价。结果表明：采用30%Fe2(SO4)3+15% 二乙醇胺+55% 水制备的新型交联剂体系，直接与磷酸酯混合即可形成油基冻胶，其性能不受放置时间的影响，交联速度快，成胶性能好，10 min 就可达到最大黏度；压裂液的抗温抗剪切性能高，与常规铝交联剂体系比较，压裂液成胶速度提高了20 倍，压裂液的抗温能力由原来100 ℃提高到135 ℃，并且压裂液的破胶性和滤失性等性能均能达到压裂施工的要求。