Predicting Insurance Losses Under Cross-Classification: A Comparison of Alternative Approaches

Various mathematical and statistical models for estimation of automobile insurance pricing are reviewed. The methods are compared on their predictive ability based on two sets of automobile insurance data for two different states collected over two different periods. The issue of model complexity versus data availability is resolved through a comparison of the accuracy of prediction. The models reviewed range from the use of simple cell means to various multiplicative-additive schemes to the empirical-Bayes approach. The empirical-Bayes approach, with prediction based on both model-based and individual cell estimates, seems to yield the best forecast.     

简单平均组合预测有效性的应用分析

通过实例分析,说明了当序列模式变动较大时,简单平均组合预测模型相对于其他组合预测模型的优越性,并且基于样本段的拟合精度不足以说明组合预测模型的外推预测精度。文中的分析对于组合预测模型的选择和应用具有实际参考价值。     

不公平有几何？——中国城市居民收入分配公平感的测量

文章首先通过批判性地介绍几种已有的公平感测量方法,选取其中最为合适的一种在CGSS2005数据基础上测量中国城市居民的反身性公平感和非反身性公平感。其次,分别以性别、年龄、教育和单位体制变量分组,从多方面呈现了两种公平感在中国的现状。最后,作者通过使用对总体样本进行随机性拆分得到的两个样本对此测量方法的信度进行了验证。     

A permutation test approach to the choice of size k for the nearest neighbors classifier

The k nearest neighbors (k-NN) classifier is one of the most popular methods for statistical pattern recognition and machine learning. In practice, the size k, the number of neighbors used for classification, is usually arbitrarily set to one or some other small numbers, or based on the cross-validation procedure. In this study, we propose a novel alternative approach to decide the size k. Based on a k-NN-based multivariate multi-sample test, we assign each k a permutation test based Z-score. The number of NN is set to the k with the highest Z-score. This approach is computationally efficient since we have derived the formulas for the mean and variance of the test statistic under permutation distribution for multiple sample groups. Several simulation and real-world data sets are analyzed to investigate the performance of our approach. The usefulness of our approach is demonstrated through the evaluation of prediction accuracies using Z-score as a criterion to select the size k. We also compare our approach to the widely used cross-validation approaches. The results show that the size k selected by our approach yields high prediction accuracies when informative features are used for classification, whereas the cross-validation approach may fail in some cases.     

A sequential conditional probability ratio test procedure for comparing diagnostic tests

In this paper, we derive sequential conditional probability ratio tests to compare diagnostic tests without distributional assumptions on test results. The test statistics in our method are nonparametric weighted areas under the receiver-operating characteristic curves. By using the new method, the decision of stopping the diagnostic trial early is unlikely to be reversed should the trials continue to the planned end. The conservatism reflected in this approach to have more conservative stopping boundaries during the course of the trial is especially appealing for diagnostic trials since the end point is not death. In addition, the maximum sample size of our method is not greater than a fixed sample test with similar power functions. Simulation studies are performed to evaluate the properties of the proposed sequential procedure. We illustrate the method using data from a thoracic aorta imaging study.     

Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index

More flexible semiparametric linear‐index regression models are proposed to describe the conditional distribution. Such a model formulation captures varying effects of covariates over the support of a response variable in distribution, offers an alternative perspective on dimension reduction and covers a lot of widely used parametric and semiparameteric regression models. A feasible pseudo likelihood approach, accompanied with a simple and easily implemented algorithm, is further developed for the mixed case with both varying and invariant coefficients. By justifying some theoretical properties on Banach spaces, the uniform consistency and asymptotic Gaussian process of the proposed estimator are also established in this article. In addition, under the monotonicity of distribution in linear‐index, we develop an alternative approach based on maximizing a varying accuracy measure. By virtue of the asymptotic recursion relation for the estimators, some of the achievements in this direction include showing the convergence of the iterative computation procedure and establishing the large sample properties of the resulting estimator. It is noticeable that our theoretical framework is very helpful in constructing confidence bands for the parameters of interest and tests for the hypotheses of various qualitative structures in distribution. Generally, the developed estimation and inference procedures perform quite satisfactorily in the conducted simulations and are demonstrated to be useful in reanalysing data from the Boston house price study and the World Values Survey.     

基于FPGA的高频等精度频率计设计与实现

文章介绍了等精度频率计误差分析和实现原理,在Altera新一代FPGA/PLD开发软件QuartusⅡ 中运用硬件描述语言Verilog HDL编程,通过单片机控制EP1 C12Q240I7芯片实现等精度频率计的设计,频率计可通过分频测量800 MHZ～1 400 MHZ之间的高频信号频率,大大提高了测量精度,实验证明测量精度为0.000 03％以下.     

农民专业合作社理事长能力测度与培育——基于运城市100家合作社的实证研究

基于运城市100家合作社的调查数据,确定测度合作社理事长能力的9个维度:政府关系能力、社会关系能力、管理能力、战略能力、创新能力、资源整合能力、学习能力、操作能力和机会能力,并对理事长能力的差异性之根源以及理事长能力的培育进行探讨。实证结果表明:在理事长能力的结构中,政府关系能力贡献最多,其次是创新能力,再次是资源整合能力,其他依次为社会关系能力、管理能力、战略能力、学习能力、操作能力和机会能力。理事长能力主要受合作社组建方式、合作社产品类型、理事长受教育程度和担任理事长的时间影响。合作社理事长能力的培育可以通过政府扶持政策、理事长自身素质的提高以及完善理事长助理制度等三方面来实现。     

基于任务的英语学习者口语准确性和流利性对比研究

对不同任务类型(复述故事和即席讲话)中29名英语学习者口语准确性和流利性的关系调查和分析表明,在复述故事中,口语准确性和流利性没有显著的相关性;在即席讲话中,口语准确性和流利性呈低度或低中度相关。t检验表明,复述故事中口语准确性显著低于即席讲话中口语准确性;流利性随测量指标的不同在任务之间呈现不同的差异模式。