浅谈中国现代史教学中正面引导问题

浅谈中国现代史教学中正面引导问题张小满中国现代史距今时间较短，政治性较强，属于争论而仍未定论的问题较多，因此，在教学中对学生进行正面引导，对于学生形成正确的历史观、世界观、价值观，正确认识今天更有其重要性和现实意义．笔者在教学实践中认识到，要作到寓思...     

曲柄滑块机构按轨迹和姿态的优化综合

本文提出的新型的共用曲柄双滑块机构,不仅精确地复演了椭圆轨迹,而且保持了执行构件的姿态在任何一点都与该点的切线垂直,因而有可能发展成一种新型的椭面加工机械,使加工出的工件的壳体表面成为真正的椭圆面。     

中学化学教学法实验教学浅谈

中学化学教学法实验教学浅谈曹书杰（南阳师专化学系，６７３０６１）中学化学教学法实验课是以中学化学实验为主要研究对象，但是它的内容决不是单纯地重复中学化学实验，而是在“探索、研究”上下功夫。它不仅要求学生掌握化学实验的基本技能，而且还要探讨和研究巾学化...     

Measuring Kurtosis by Right and Left Inequality Orders

The question of how to measure kurtosis in both symmetric and asymmetric distributions is addressed using the kurtosis diagram of Zenga (2006 Zenga , M. ( 2006 ). Kurtosis . In : Kotz , S. , Read , C. B. , Balakrishnan , N. , Vidakovic , B. , eds. Encyclopedia of Statistical Sciences. 2nd ed . New York : John Wiley and Sons . [Google Scholar]). Kurtosis is related to inequality at either side of the median, and we establish a hierarchy of kurtosis orderings in which the kurtosis diagram stands at the weakest level. A sufficient condition for constructing kurtosis measures compatible with such ordering is provided. The merits of the proposed approach in both clarifying and formalizing the idea of kurtosis are evaluated and examples are discussed throughout.     

Robustness of Approaches to ROC Curve Modeling under Misspecification of the Underlying Probability Model

A variety of statistical regression models have been proposed for the comparison of ROC curves for different markers across covariate groups. Pepe developed parametric models for the ROC curve that induce a semiparametric model for the market distributions to relax the strong assumptions in fully parametric models. We investigate the analysis of the power ROC curve using these ROC-GLM models compared to the parametric exponential model and the estimating equations derived from the usual partial likelihood methods in time-to-event analyses. In exploring the robustness to violations of distributional assumptions, we find that the ROC-GLM provides an extra measure of robustness.     

Nonparametric boundary detection

We propose a two-step nonparametric method for detecting the boundary curve of an object in an image. First we treat boundary points as change-points on lines across the image, and identify them by the one-sided kernel smoothing method. After obtaining potential boundary points, we use the principal curve method to smooth these points in order to obtain an estimate of smooth boundary curve, Computer simulations are provided to illustrate the effectiveness of the method.     

On the use of curve fitting to model the error of the Cornish-Fisher expansion of the pearson type-VI distribution

The Cornish-Fisher expansion of the Pearson type VI distribution is known to be reasonably accurate when both degrees of freedom are relatively large (say greater than or equal to 5). However, when either or both degrees of freedom are less than 5, the accuracy of the computed percentage point begins to suffer; in some cases severely. To correct for this, the error surface in the degrees of freedom plane is modeled by least squares curve fitting for selected levels of tail probability (.025, .05, and .10) which can be used to adjust the percentage point obtained from the usual Cornish-Fisher expansion. This adjustment procedure produces a computing algorithm that computes percentage points of the Pearson type VI distribution at the above probability levels, accurate to at least + 1 in 3 digits in approximately 11 milliseconds per subroutine call on an IBM 370/145. This adjusted routine is valid for both degrees of freedom greater than or equal to 1.     

An Introduction to Ranking and Selection

This expository paper explains the philosophy of the indifference-zone approach and the subset-selection approach to ranking and selection procedures. It includes examples of operating characteristic curves and data applications for selection problems based on the binomial and normal distributions. A variety of different models and goals are provided with a list of references.     

Developing a variables repetitive group sampling plan based on process capability index C pk with unknown mean and variance

In this paper, variables repetitive group sampling plans are developed based on the process capability index C _pk when the quality characteristic follows a normal distribution with unknown mean and variance. The sampling plan parameters such as the sample size and the acceptance constant are determined to minimize the average sample number. Symmetric and asymmetric cases, in percent defectives due to two specification limits, are dealt with for specified combinations of acceptable quality level and limiting quality level. Tables are provided and examples are given to use proposed plans in practice.     

Semiparametric ROC surface estimation for continuous diagnostic tests via polytomous logistic regression procedures

In this paper, we propose a semiparametric method of estimating receiver operating characteristic (ROC) surfaces for continuous diagnostic tests under density ratio models. Implementation of our method is easy since the usual polytomous logistic regression procedures in many statistical software packages can be employed. A simulated example is provided to facilitate the implementation of our method. Simulation results show that the proposed semiparametric ROC surface estimator is more efficient than the nonparametric counterpart and the parametric counterpart whether the normality assumption of data holds or not. Moreover, some simulation results on the underlying semiparametric distribution function estimators are also reported. In addition, some discussions on the proposed method as well as analysis of a real data set are provided.