关于加强河北省高校教师队伍建设的思考

"十五"期间河北省高校教师队伍建设取得了很大成绩,但与发达省市相比仍有一定差距,不能满足建设沿海经济社会发展强省的需要。本文从加强教师职业道德建设、实施"高层次创造性人才工程"、优化教师资源配置、强化教师培训、深化高校人事分配制度改革等五个方面提出了加强河北省高校教师队伍建设的对策和建议。     

Projection de hájek et polynômes de bernstein

Under the hypothesis of white noise, the authors derive the explicit form of the asymptotic representation of linear rank statistics resulting from Hájek's (1968) celebrated projection lemma for linear rank statistics in the so‐called approximate score case. This representation based on Bernstein polynomials is better, in the quadratic mean sense, than the traditional one due to Hájek (1961, 1962). The polynomial representation allows for a new derivation of classical asymptotic results (asymptotic normality, Berry‐Essten bounds). Moreover, a simulation study shows that the quality of the polynomial approximation to the exact finite‐sample distributions of rank statistics is sizeably better than that resulting from the traditional approach.     

Functional linear discriminant analysis for irregularly sampled curves

We introduce a technique for extending the classical method of linear discriminant analysis (LDA) to data sets where the predictor variables are curves or functions. This procedure, which we call functional linear discriminant analysis ( FLDA ), is particularly useful when only fragments of the curves are observed. All the techniques associated with LDA can be extended for use with FLDA. In particular FLDA can be used to produce classifications on new (test) curves, give an estimate of the discriminant function between classes and provide a one- or two-dimensional pictorial representation of a set of curves. We also extend this procedure to provide generalizations of quadratic and regularized discriminant analysis.     

保反零积线性映射

给出了Ｂ（Ｘ）到Ｂ（Ｙ）上保反零积线性映射的具体形式     

Tests for cointegration rank and choice of the alternative

This paper discusses likelihood-ratio (LR) tests on the cointegrating (CI) rank which consider any possible dimension of the CI rank under the alternative. The trace test and lambda-max test are obtained as special cases. Limit quantiles for all the tests in the class are derived. It is found that any of these tests can be used to construct an estimator of the CI rank, with no differences in asymptotic properties when the alternative is fixed. The properties of the class of tests are investigated by local asymptotic analysis, a simulation study and an empirical illustration. It is found that all the tests in the class have comparable power, which deteriorates substantially as the number of random walks increases. Tests constructed for a specific class of alternatives present minor power gains for alternatives in the class, and require the alternative to be far from the null. No test in this class is found to be asymptotically (in-)admissible. Some of the new tests in the class can also be arranged to give a constrained estimator of the CI rank, that restricts the minimum number of common trends. The power gains that these tests can obtain by constraining the minimum number of common trends appears to be limited and outweighted by the risk of inconsistency induced by the constrains. As a consequence, no value of the CI rank should be left untested, unless it can be excluded beyond any reasonable doubt.     

Log‐rank permutation tests for trend: saddlepoint p‐values and survival rate confidence intervals

Suppose p + 1 experimental groups correspond to increasing dose levels of a treatment and all groups are subject to right censoring. In such instances, permutation tests for trend can be performed based on statistics derived from the weighted log‐rank class. This article uses saddlepoint methods to determine the mid‐P‐values for such permutation tests for any test statistic in the weighted log‐rank class. Permutation simulations are replaced by analytical saddlepoint computations which provide extremely accurate mid‐P‐values that are exact for most practical purposes and almost always more accurate than normal approximations. The speed of mid‐P‐value computation allows for the inversion of such tests to determine confidence intervals for the percentage increase in mean (or median) survival time per unit increase in dosage. The Canadian Journal of Statistics 37: 5‐16; 2009 © 2009 Statistical Society of Canada     

略论唐代宗室制度及其影响

唐代宗室可由爵位出官,亦可由血缘关系出官。以爵位出官,《旧唐书》、《新唐书》的记载清晰准确,《唐六典》与《唐会要》的记述则比较模糊。以爵出官的品阶也与实际情况有所差距。若以血缘关系出官,宗室的五等血缘品阶与其出官品阶并不一一对应。唐代的宗室政策,在高祖时延续隋制,从太宗开始,保持近房宗室的政治地位,压制远房宗室。玄宗以后,近房宗室基本不出阁,远房宗室则与异姓之臣杂而仕宦。在对政局的影响上,唐代宗室整体素质较低,影响是消极的。     

图嵌入下稀疏低秩集成预测的多因子资产选择策略

面对金融市场的大量不确定性因素,如何合理选择有效的定价因子并构建科学的资产定价体系,一直是金融理论研究的核心问题之一。本文利用图嵌入的方法,基于稀疏表示和低秩表示策略,深度挖掘潜含在数据集中的内在结构,构建了能够同时揭示数据局部结构信息和全局结构信息的集成学习策略,以实现不同维度的多源数据融合。从CAPM和APT理论出发,通过集成预测的方法构建量化多因子资产选择模型,代表性地选择了卷积神经网络、梯度提升决策树、时间序列及支持向量机等模型进行单一预测,并通过稀疏低秩的图近似最小二乘回归集成策略进行优化。实证结果表明基于集成预测的稀疏低秩策略其资产选择能力更强,超额收益率更高。采用机器学习的非线性预测方法更有利于揭示金融系统的复杂特性。实证结论对投资组合管理具有重要指导意义。     

Threshold knot selection for large-scale spatial models with applications to the Deepwater Horizon disaster

Large spatial datasets are typically modelled through a small set of knot locations; often these locations are specified by the investigator by arbitrary criteria. Existing methods of estimating the locations of knots assume their number is known a priori, or are otherwise computationally intensive. We develop a computationally efficient method of estimating both the location and number of knots for spatial mixed effects models. Our proposed algorithm, Threshold Knot Selection (TKS), estimates knot locations by identifying clusters of large residuals and placing a knot in the centroid of those clusters. We conduct a simulation study showing TKS in relation to several comparable methods of estimating knot locations. Our case study utilizes data of particulate matter concentrations collected during the course of the response and clean-up effort from the 2010 Deepwater Horizon oil spill in the Gulf of Mexico.     

Cancer immunotherapy trial design with delayed treatment effect

A challenge arising in cancer immunotherapy trial design is the presence of a delayed treatment effect wherein the proportional hazard assumption no longer holds true. As a result, a traditional survival trial design based on the standard log‐rank test, which ignores the delayed treatment effect, will lead to substantial loss of statistical power. Recently, a piecewise weighted log‐rank test is proposed to incorporate the delayed treatment effect into consideration of the trial design. However, because the sample size formula was derived under a sequence of local alternative hypotheses, it results in an underestimated sample size when the hazard ratio is relatively small for a balanced trial design and an inaccurate sample size estimation for an unbalanced design. In this article, we derived a new sample size formula under a fixed alternative hypothesis for the delayed treatment effect model. Simulation results show that the new formula provides accurate sample size estimation for both balanced and unbalanced designs.