关于考试成绩正态分布绝对化的悖论——基于长春市某理工类高校大学英语四级考试成绩的个案分析

通过对长春市某理工类高校本科生及研究生大学英语四级考试成绩分布样态以及相关数据的量化分析，探究考试成绩正态分布绝对化在该校大学英语四级考试成绩分布评价中的不合理性。指出应辩证地看待正态分布在教学质量评价体系中的作用，尤其还应当重视考试成绩呈偏态分布的情况，并从中挖掘教育潜在资源和信息，从而切实提高大学英语教学水平。     

堆垒级数部分和的一般公式

利用阶乘幂差分的重要性质,得到堆垒级数部分和的一般公式.     

要约收购分类研究

从收购方发出收购要约是自愿还是法律强制规定等几个角度对要约收购分类进行详细阐述，使各国在对要约收购方式立法时能根据本国国情有所选择、有所侧重，从而将资源优化配置与中小股东权益保护相结合，实现效率与公平在立法及实施上的平衡。     

李家坝煤矿斜井开拓局部冻结关键技术研究

斜井冻结技术尚处于摸索研究阶段，国内无统一的施工规范。在李家坝煤矿斜井冻结工程实践的基础上开展应用性研究，详细阐述了斜井局部冻结的设计原则、施工关键技术，尤其是快速造孔施工及冻结管保温层施工工艺，提出了冻结管保温接头处理方式，成功应用了斜井冻结步进式投入法，解决了斜井局部冻结关键技术，为类似局部冻结工程提供了借鉴和参考。     

Asymptotic behaviour of a test statistic for detection of change in mean of vectors

The paper gives an asymptotic distribution of a test statistic for detecting a change in a mean of random vectors with dependent components. The studied test statistic has a form of a maximum of a square Euclidean norms of vectors with components being standardized partial cumulative sums of deviations from means. The limit distribution was obtained using a result of Piterbarg [1994. High deviations for multidimensional stationary Gaussian processes with independent components. In: Zolotarev, V.M. (Ed.), Stability Problems for Stochastic Models, pp. 197–210].     

Multistate life‐tables and regression models

A survey is given of the use of modern statistical techniques in event history analysis, and in particular in the study of multi‐state life‐tables in demography. Emphasis is placed on the interplay between partial likelihood and nonparametric maximum likelihood based methods, a) when analysing semi‐Markov models or models with repeated spells, and b) in frailty models for inobservable heterogeneity.     

化学热力学函数偏微商等式证明方法探讨

从基础热力学函数的相互关系出发，结合偏微商运算基本原理，归纳热力学函数偏微商变换的常用途径，并对化学热力学函数偏微商式的证明方法及技巧进行一些具体研讨。     

Dimensionality reduction approach to multivariate prediction

The authors consider dimensionality reduction methods used for prediction, such as reduced rank regression, principal component regression and partial least squares. They show how it is possible to obtain intermediate solutions by estimating simultaneously the latent variables for the predictors and for the responses. They obtain a continuum of solutions that goes from reduced rank regression to principal component regression via maximum likelihood and least squares estimation. Different solutions are compared using simulated and real data.     

Asymptotic Analysis of the Sieve Estimator for a Class of Parabolic SPDEs

In this paper we consider the problem of estimating a coefficient of a strongly elliptic partial differential operator in stochastic parabolic equations. The coefficient is a bounded function of time. We compute the maximum likelihood estimate of the function on an approximating space (sieve) using a finite number of the spatial Fourier coefficients of the solution and establish conditions that guarantee consistency and asymptotic normality of the resulting estimate as the number of the coefficients increases. The equation is assumed diagonalizable in the sense that all the operators have a common system of eigenfunctions.     

Smoothing for discrete-valued time series

We deal with smoothed estimators for conditional probability functions of discrete-valued time series { Y_t } under two different settings. When the conditional distribution of Y_t given its lagged values falls in a parametric family and depends on exogenous random variables, a smoothed maximum (partial) likelihood estimator for the unknown parameter is proposed. While there is no prior information on the distribution, various nonparametric estimation methods have been compared and the adjusted Nadaraya–Watson estimator stands out as it shares the advantages of both Nadaraya–Watson and local linear regression estimators. The asymptotic normality of the estimators proposed has been established in the manner of sparse asymptotics, which shows that the smoothed methods proposed outperform their conventional, unsmoothed, parametric counterparts under very mild conditions. Simulation results lend further support to this assertion. Finally, the new method is illustrated via a real data set concerning the relationship between the number of daily hospital admissions and the levels of pollutants in Hong Kong in 1994–1995. An ad hoc model selection procedure based on a local Akaike information criterion is proposed to select the significant pollutant indices.