On detecting outliers in the Pareto distribution

In this paper, we introduce two new statistics for detecting outliers in the Pareto distribution. These new statistics are the extension of the statistics for detecting outliers in exponential and gamma distributions. In fact, we compare the power of our test statistics with the other statistics and select the best test statistic for detecting outliers in the Pareto distribution. Finally, numerical examples of different insurance claims are used to see the performance of the test.     

Skewed zero-bound distributions and process capability indices for upper specifications

A common practical situation in process capability analysis, which is not well developed theoretically, is when the quality characteristic of interest has a skewed distribution with a long tail towards relatively large values and an upper specification limit only exists. In such situations, it is not uncommon that the smallest possible value of the characteristic is 0 and this is also the best value to obtain. Hence a target value 0 is assumed to exist. We investigate a new class of process capability indices for this situation. Two estimators of the proposed index are studied and the asymptotic distributions of these estimators are derived. Furthermore, we suggest a decision procedure useful when drawing conclusions about the capability at a given significance level, based on the estimated indices and their asymptotic distributions. A simulation study is also performed, assuming that the quality characteristic is Weibull-distributed, to investigate the true significance level when the sample size is finite.     

语言相对论研究述评

从时间、色彩、位值与运动事件等四个方面介绍与述评国外近期对萨丕尔．沃尔夫假说的实证研究，同时结合国内一些学者的成果，来探讨语言与思维之间的关系。     

Bayesian Analysis of Multiple Hypothesis Testing with Applications to Microarray Experiments

Recently, the field of multiple hypothesis testing has experienced a great expansion, basically because of the new methods developed in the field of genomics. These new methods allow scientists to simultaneously process thousands of hypothesis tests. The frequentist approach to this problem is made by using different testing error measures that allow to control the Type I error rate at a certain desired level. Alternatively, in this article, a Bayesian hierarchical model based on mixture distributions and an empirical Bayes approach are proposed in order to produce a list of rejected hypotheses that will be declared significant and interesting for a more detailed posterior analysis. In particular, we develop a straightforward implementation of a Gibbs sampling scheme where all the conditional posterior distributions are explicit. The results are compared with the frequentist False Discovery Rate (FDR) methodology. Simulation examples show that our model improves the FDR procedure in the sense that it diminishes the percentage of false negatives keeping an acceptable percentage of false positives.     

评思维语言假说的当代论争

思维语言假说(LOTH)的当代论争主要体现在两方面:一方面,该假说的主要反对者从思维语言的语义、解释功能及其关键特征等入手,试图推翻思维语言假说;另一方面,福多本人以及大多数学者从心理学、语言学、认知科学等学科的交叉研究成果角度极力为思维语言假说辩护.     

空气冲旋钻头牙齿失效分析与新材料实验研究

针对目前空气冲旋钻头钻进中牙齿频繁断裂、脱落以及磨损严重，导致破岩效率低、使用寿命短等问题，采用纳米改型技术，在硬质合金中掺杂纳米Al₂O₃制备出Al₂O₃/WC Co纳米/微米复合材料，对其性能、组织结构进行分析，对其耐磨性、耐冲击性进行实验研究，结果表明：加入3%的纳米Al₂O₃并添加适量的抑制剂和稀土元素能明显改善Al₂O₃/WC Co纳米/微米复合材料的组织结构、细化晶粒，复合材料的耐磨性和耐冲击性能得到大幅提高，较硬质合金YG8提高4～8倍。为大幅度提高钻头破岩效率，延长钻头使用寿命提供了可能性。     

预期收益最大化与“蚁族”现象

蚁族现象的本质是大学毕业生选择在大城市还是中小城镇就业的问题。从理性人假设的角度来看,"蚁族"现象的原因在于"蚁族"们为了获得更多的就业机会、更高的就业质量等经济收益,和更多的教育收益、消费收益、心理收益和健康收益等非经济收益,从而主动选择在大城市就业的结果。减少"蚁族"现象的思路在于提高大学毕业生收入、促进教育公平和均衡发展、重视发展中小城镇、引导大学毕业生到中小城镇就业。     

关键期假设与外语教学

Lenneberg的关键期假设使人们意识到年龄对学习语言的影响。本文认为要正确理解该假设在第二语言习得中的运用 ;根据我国的实际情况 ,建议正式学习外语的最佳年龄应确定于 1 2岁 ,并对小学外语教育提出自己的看法     

Assessing the Precision of Turning Point Estimates in Polynomial Regression Functions

Researchers often report point estimates of turning point(s) obtained in polynomial regression models but rarely assess the precision of these estimates. We discuss three methods to assess the precision of such turning point estimates. The first is the delta method that leads to a normal approximation of the distribution of the turning point estimator. The second method uses the exact distribution of the turning point estimator of quadratic regression functions. The third method relies on Markov chain Monte Carlo methods to provide a finite sample approximation of the exact distribution of the turning point estimator. We argue that the delta method may lead to misleading inference and that the other two methods are more reliable. We compare the three methods using two data sets from the environmental Kuznets curve literature, where the presence and location of a turning point in the income-pollution relationship is the focus of much empirical work.