神经元网络在SAS中的实现(Ⅰ)

大多数常见的人工神经元网络—多层感知器（ＭＬＰ），无非是非线性回归以及判别模型。其训练方法通常是适合大型并行机硬件实现的梯度下降算法。对于一般的计算环境，ＳＡＳ系统中若干优化算法远比神经元网络的并行算法更有效。本文解释神经元网络是什么，描述神经元网络与统计模型的关系，介绍神经元网络在ＳＡＳ中的实现。     

变量重排优化Groebner基运算的研究

本文通过使用变量重排的方法,改变了多项式环中理想的Groebner基的计算过程,得到不同的过程的计算效率也不同,因此通过这种方法应该能够找出减少计算Groebner基时间的方法．     

粗糙集的相似度量

在近似空间中,分别以集合的上下近似以及元素的隶属度定义了两个集合间的相似度度量,讨论了两种相似度的性质,并对两种相似度进行了比较．     

灰色统计在人员素质评估中的应用

本文介绍了灰色统计的方法，并利用灰色统计的方法对教员素质进行了评估，它开辟了人员汞质评估的新途径。     

运用基因型统计量对数量性状位点进行关联分析

随着基因分型技术的不断发展,遗传学家可以获得大量遗传标记的基因型和单体型数据,这为鉴定人类复杂疾病基因提供了前所未有的机会。当不能直接获得单体型数据时,可以使用基因型数据的统计方法来进行关联分析．使用基因型数据对疾病基因进行关联分析的统计方法可以扩充到定位数量性状位点（QTL）。本文扩充了对疾病基因进行关联分析的主成份分析统计量PG咒和熵统计量％。到数量性状,利用选择基因型对QTL进行关联分析。计算机模拟考察了两个统计量的I型错误率．基于10个遗传性血色病（Hereditaryhaemochromatosis）单体型频率的计算机模拟调查了两个统计量的统计功效．结果表明两个统计量PCTt和TGE可以有效地对QTL进行关联分析．     

居民消费的典型相关分析

本文介绍了典型相关的基本思想 ,对居民消费与税收等指标之间的相互关系作典型相关分析 ,并就其间的因素影响进行讨论。     

科技进步贡献率测算方法的研究与应用

本文针对我国的统计现状对科技进步贡献率测算方法进行了研究，提出了一套适合现行统计体系的科技进步贡献率测算方法，并用此方法对安徽省1994年的工业、农业及全社会的科技进步贡献率进行了测算。     

中国各地区现代化的因子分析及非均衡差异研究

本文依据构建的中国地区现代化指标体系对中国31个地区25个指标进行了因子分析及非均衡差异研究,得出了中国各地区现代化水平具有了非均衡性、整体偏低性和梯度演变性结论,从而提出了不同区域集团应采取有差别的现代化战略.     

《概率论与数理统计》课程成绩统计分析与教学策略

利用偏度、峰度检验法,针对三年中《概率论与数理统计》课程的考试成绩,分六个学期,详细地检验了成绩总体是否服从正态分布,绘制了直方图.深刻地分析了成绩发生异常情况的原因以及应该采取的教学策略.统计结果带有广泛的普遍性.     

半参数广义线性模型的影响分析与异常点检验

统计诊断就是对统计推断方法解决问题的全过程进行诊断，而影响分析是统计诊断中十分重要的分支．本文针对半参数广义线性模型，证明了数据删除模型和均值漂移模型的等价性定理，给出了诸如广义Cook距离等诊断统计量并研究了异常点的Score检验统计量，最后通过实例验证了本文给出的诊断方法的有效性。     

Controversies Around the Role of Statistical Tests in Experimental Research

Despite widespread use of significance testing in empirical research, its interpretation and researchers' excessive confidence in its results have been criticized for years. In this article, the logic of statistical testing in the Fisher and Neyman-Pearson approaches are described, some common misinterpretations of basic concepts behind statistical tests are reviewed, and the philosophical and psychological issues that can contribute to these misinterpretations are analyzed. Some frequent criticisms against statistical tests are revisited, with the conclusion that most of them refer not to the tests themselves but to the misuse of tests on the part of researchers. In accordance with Levin (1998a), statistical tests should be transformed into a more intelligent process that helps researchers in their work. Possible ways in which statistical education might contribute to the better understanding and application of statistical inference are suggested.     

Controversies Around the Role of Statistical Tests in Experimental Research

Despite widespread use of significance testing in empirical research, its interpretation and researchers' excessive confidence in its results have been criticized for years. In this article, the logic of statistical testing in the Fisher and Neyman-Pearson approaches are described, some common misinterpretations of basic concepts behind statistical tests are reviewed, and the philosophical and psychological issues that can contribute to these misinterpretations are analyzed. Some frequent criticisms against statistical tests are revisited, with the conclusion that most of them refer not to the tests themselves but to the misuse of tests on the part of researchers. In accordance with Levin (1998a), statistical tests should be transformed into a more intelligent process that helps researchers in their work. Possible ways in which statistical education might contribute to the better understanding and application of statistical inference are suggested.     

Large-deviation theorems in hypothesis-testing problems

Large-deviation theorems of Chernoff type for the logarithm of the likelihood ratio in general binary statistical experiments are obtained. The obtained limit theorems are used to investigate of the rate of decrease of the error probabilities for Neyman-Pearson tests, Bayes tests, and minimax tests in statistical experiments generated by normal autoregressive processes and Galton-Watson processes with immigration. Proceedings of the Seminar on Stability Problems for Stochastic Models, Vologda, Russia, 1998, Part II.     

Cryptographic pseudo-random sequence from the spatial chaotic map

A scheme for pseudo-random binary sequence generation based on the spatial chaotic map is proposed. In order to face the challenge of using the proposed PRBS in cryptography, the proposed PRBS is subjected to statistical tests which are the well-known FIPS-140-1 in the area of cryptography, and correlation properties of the proposed sequences are investigated. The proposed PRBS successfully passes all these tests. Results of statistical testing of the sequences are found encouraging. The results of statistical tests suggest strong candidature for cryptographic applications.     

Markov chain test for time dependence and homogeneity: An analytical and empirical evaluation

This paper evaluates the small and large sample properties of Markov chain time-dependence and time-homogeneity tests. First, we present the Markov chain methodology to investigate various statistical properties of time series. Considering an auto-regressive time series and its associated Markov chain representation, we derive analytical measures of the statistical power of the Markov chain time-dependence and time-homogeneity tests. We later use Monte Carlo simulations to examine the small-sample properties of these tests. It is found that although Markov chain time-dependence test has desirable size and power properties, time-homogeneity test does not perform well in statistical size and power calculations.     

Model selection in Neural Networks: Some difficulties

This paper considers two related issues regarding feedforward Neural Networks (NNs). The first involves the question of whether the network weights corresponding to the best fitting network are unique. Our empirical tests suggest an answer in the negative, whether using standard Backpropagation algorithm or our preferred direct (non-gradient-based) search procedure. We also offer a theoretical analysis which suggests that there will almost inevitably be functional relationships between network weights. The second issue concerns the use of standard statistical approaches to testing the significance of weights or groups of weights. Treating feedforward NNs as an interesting way to carry out nonlinear regression suggests that statistical tests should be employed. According to our results, however, statistical tests can in practice be indeterminate. It is rather difficult to choose either the number of hidden layers or the number of nodes on this basis.     

Comparative analysis of the power of goodness-of-fit tests for near competing hypotheses. I. The verification of simple hypotheses

Using statistical modeling methods, we analyze the power of a series of goodness-of-fit tests for simple and complex hypotheses. The estimates we give for the power of the tests for simple hypotheses versus some near competing hypotheses enable us to rank the goodness-of-fit tests.     

Few statistical tests for proportions comparison

This article reviews a number of statistical tests for comparing proportions. These statistical tests are presented in a comprehensive way, so that OR practitioners can easily understand them and correctly use them. A test for 2 × 2 contingency tables is developed and shown to be more powerful than other classical tests of the literature such as Fisher’s exact test. Tables with critical values for small samples are provided, so that the test can be conducted without any computations.     

Comparative analysis of the power of goodness-of-fit tests for near competing hypotheses. II. Verification of complex hypotheses

In this part of the article, we use the statistical modeling methods to analyze the power of a series of goodness-of-fit tests for complex hypotheses. We estimate the power of tests relative to some near competing hypotheses. The combination of results enables us to order the tests with respect to their power for testing both simple and complex hypotheses.     

Nonparametric Methods for Checking the Validity of Prior Order Information

A large number of statistical procedures have been proposed in the literature to explicitly utilize available information about the ordering of treatment effects at increasing treatment levels. These procedures are generally more efficient than those ignoring the order information. However, when the assumed order information is incorrect, order restricted procedures are inferior and, strictly speaking, invalid. Just as any statistical model needs to be validated by data, order information to be used in a statistical analysis should also be justified by data first. A common statistical format for checking the validity of order information is to test the null hypothesis of the ordering representing the order information. Parametric tests for ordered null hypotheses have been extensively studied in the literature. These tests are not suitable for data with nonnormal or unknown underlying distributions. The objective of this study is to develop a general distribution-free testing theory for ordered null hypotheses based on rank order statistics and score generating functions. Sufficient and necessary conditions for the consistency of the proposed general tests are rigorously established.