On Graphing Paired Data

Techniques for graphing paired data are considered. A conventional method frequently used when reporting scientific results, particularly in medical journals, involves representing pairs of measurements by straight line segments titled at different angles related to the differences between the components of the data pairs. However when the sample size is only moderately large, this type of display can become cluttered and thus uninformative due to overlap. It is suggested that a new graph that combines features of ANOVA plots and multivalued dot charts may provide a more effective visual display of paired data. A designed experiment in data perception using simulated data provides some evidence in favor of this parallel line plot.     

Bayes sequential estimation for a Poisson process under a LINEX loss function

In this paper, within the framework of a Bayesian model, we consider the problem of sequentially estimating the intensity parameter of a homogeneous Poisson process with a linear exponential (LINEX) loss function and a fixed cost per unit time. An asymptotically pointwise optimal (APO) rule is proposed. It is shown to be asymptotically optimal for the arbitrary priors and asymptotically non-deficient for the conjugate priors in a similar sense of Bickel and Yahav [Asymptotically pointwise optimal procedures in sequential analysis, in Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, University of California Press, Berkeley, CA, 1967, pp. 401–413; Asymptotically optimal Bayes and minimax procedures in sequential estimation, Ann. Math. Statist. 39 (1968), pp. 442–456] and Woodroofe [A.P.O. rules are asymptotically non-deficient for estimation with squared error loss, Z. Wahrsch. verw. Gebiete 58 (1981), pp. 331–341], respectively. The proposed APO rule is illustrated using a real data set.     

Regression imputation with Q-mode clustering for rounded zero replacement in high-dimensional compositional data

The logratio methodology is not applicable when rounded zeros occur in compositional data. There are many methods to deal with rounded zeros. However, some methods are not suitable for analyzing data sets with high dimensionality. Recently, related methods have been developed, but they cannot balance the calculation time and accuracy. For further improvement, we propose a method based on regression imputation with Q-mode clustering. This method forms the groups of parts and builds partial least squares regression with these groups using centered logratio coordinates. We also prove that using centered logratio coordinates or isometric logratio coordinates in the response of partial least squares regression have the equivalent results for the replacement of rounded zeros. Simulation study and real example are conducted to analyze the performance of the proposed method. The results show that the proposed method can reduce the calculation time in higher dimensions and improve the quality of results.     

硅胶基吸附材料的合成方法

硅胶基吸附材料是以硅胶为基质合成的一种对金属离子具有良好吸附性能的材料．本文从改性机理和合成路径两方面综述了硅胶基吸附材料的合成方法,并讨论了不同合成路径（异相法、均相法、共聚法）的优缺点．     

“十二五” 规划中“包容性增长”概念探析

“包容性增长”包括经济、政治、文化、社会、生态等各个方面,经济增长与其他各方面的增长应该是互相协调、和谐增长、可持续增长和科学增长;经济增长的同时,财富公平分配,不造成贫富差距,向低收入人群倾斜,使所有人都从增长中获益。文章旨在通过对“包容性增长”概念之阐释,以更好地理解“包容性增长”的深刻含义,促进经济变革与社会更好更快地发展。     

具有Neumann边值的齐次p-Laplacian方程的指标分类理论

通过建立指标分类理论讨论了一维p-Laplacian方程(φp(u′))′+q(t)φp(u)=0,a.e on[0,1]在Neumann边值u′(0)=0=u′(1)条件下平凡解和非平凡解的存在性,其中φp(s)=s p-2s,p>1,q∈L∞(0,1)。     

三阶线性齐次微分方程解的Sturm比较定理

研究了一类三阶线性齐次微分方程解的Sturm比较定理的理论,在三阶线性齐次微分方程的Sturm基本定理的基础上得出了Sturm比较定理,所得结论推广了现有文献的相应结果。     

私人刑事调查与侦查之比较

私人刑事调查作为自我保护与私力救济的重要手段,它同侦查存在着紧密联系。经过分析比较发现,一方面私人刑事调查与侦查有着明显同质性,这多涵盖最终目的、历史起源和启用手段种类三部分。另一方面它们二者又存在明显异质性,这主要包括基本性质、实施主体、启用手段比重、直接目的、运作范围、具体程序及受众心理七方面。     

Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions

For vectors z and w and scalar v, let r(v, z, w) be a function that can be nonparametrically estimated consistently and asymptotically normally, such as a distribution, density, or conditional mean regression function. We provide consistent, asymptotically normal nonparametric estimators for the functions G and H, where r(v, z, w) = H[vG(z), w], and some related models. This framework encompasses homothetic and homothetically separable functions, and transformed partly additive models r(v, z, w) = h[v + g(z), w] for unknown functions gand h Such models reduce the curse of dimensionality, provide a natural generalization of linear index models, and are widely used in utility, production, and cost function applications. We also provide an estimator of Gthat is oracle efficient, achieving the same performance as an estimator based on local least squares when H is known.