逆高斯分布变异系数和尺度参数的统计推断研究

构造了逆高斯分布中变异系数的广义枢轴量,给出了一种参数的区间估计方法,并与MOVOER(method of variance of estimates recovery)和Bootstrap 方法进行比较;给出了多总体下尺度参数两两差的同时置信区间.模拟结果表明:在中、小样本情况下,所给的广义置信区间其覆盖概率接近置信...     

多个偏正态总体共同位置参数的Bootstrap置信区间

该文基于Bootstrap 方法研究多个偏正态总体共同位置参数的区间估计和假设检验问题.首先,分别给出未知参数的矩估计和极大似然估计.其次,将徐礼文[1]对多个正态总体共同均值的探讨推广到多个偏正态总体,进而构造共同位置参数的Bootstrap 置信区间和Bootstrap检验统计量.Monte Carlo模拟结果表明...     

基于Bootstrap方法的VaR区间估计

本文介绍了非参数方法中基于自助法的三种区间的估计方法,并将它们应用到金融资产的VaR计算上.自助法很好地克服了历史模拟法的一些局限性.本文对上证综合指数(IA0001)进行了VaR计算的实证分析,计算了VaR点估计和区间估计,并比较了几种计算方法各自的特点,得出了一些有意义的结果.     

Bootstrap in Markov-sequences based on estimates of transition density

We develop a Bootstrap method in Markov-sequences. This method is based on kernel estimates of the transition density of the Markov-sequence. It is shown that the Bootstrap estimate of the variance of a statistic which is a function of means, is consistent. We also show that the Bootstrap distributions of mean-like statistics and von Mises differentiable statistics converge to appropriate normal distributions. A few simulation results are reported to illustrate the discussion.Most of this work was carried out when the author was at the Department of Statistics, Pennsylvania State University.     

Preservice elementary teachers’ knowledge for teaching the associative property of multiplication: A preliminary analysis

This study examines preservice elementary teachers’ (PTs) knowledge for teaching the associative property (AP) of multiplication. Results reveal that PTs hold a common misconception between the AP and commutative property (CP). Most PTs in our sample were unable to use concrete contexts (e.g., pictorial representations and word problems) to illustrate AP of multiplication conceptually, particularly due to a fragile understanding of the meaning of multiplication. The study also revealed that the textbooks used by PTs at both the university and elementary levels do not provide conceptual support for teaching AP of multiplication. Implications of findings are discussed.     

Bootstrap tests in correspondence analysis

A bootstrap test is developed for testing models specified by Goodman in 1985 and 1986 for the correspondence analysis of two-way contingency tables. It enables testing goodness-of-fit in relation with the usual matrix decomposition method. An approximate table of critical values for the proposed test statistic is presented. Bootstrap confidence interval construction is also included. The behaviour of the test statistic and the confidence intervals is studied using Monte Carlo simulation.     

Empirical likelihood method for intermediate quantiles

Intermediate quantiles play an important role in the statistics of extremes with particular applications in risk management. For interval estimation of quantiles, Chen and Hall (1993) proposed the so-called smoothed empirical likelihood method. In this paper, we apply the method in Chen and Hall (1993) to construct confidence intervals for an intermediate quantile by deriving the corresponding Wilks Theorem.     

Alternative interval estimation for parameters of bivariate exponential model with time varying covariate

This paper investigates several alternative methods of constructing confidence interval estimates based on the bootstrap and jackknife techniques for the parameters of a parallel two-component system model with dependent failure and a time varying covariate, when data is censored. This model is an extension of the bivariate exponential model. Bootstrap confidence interval techniques, the bootstrap-t, bootstrap-percentile and BCa methods are compared with the confidence interval based on the jackknife via coverage probability study using simulated data. The results clearly indicate that the jackknife technique works far better than any of the bootstrap techniques when dealing with censored data.     

协方差矩阵的齐性检验

基于ＰＰ技术、Ｂｏｏｔｓｔｒａｐ方法和数论方法,对于ｋ个总体协方差矩阵相等的检验,给出了ＰＰ型检验统计量,并讨论了它的渐近分布和Ｂｏｏｔｓｔｒａｐ逼近,最后给出了一些实际模拟结果。     

小样本下相关系数的检验与区间估计——基于Bootstrap的研究

本文首先介绍了样本相关系数的计算公式以及在联合正态分布下的假设检验和区间估计方法,同时指出了其对样本的要求,然后就小样本下相关系数的区间估计和假设检验问题给出了基于bootstrap方法的解决途径,分析表明bootstrap方法非常适合用于未知总体分布形态小样本下的区间估计与假设检验。     

基于投影绝对中位离差的分布相等性检验

为检验两个分布的相等，我们给出基于投影寻踪、Bootstrap方法和数论方法的统计量，并讨论它的极限分布和Bootstrap逼近。最后我们给出一些模拟。     

E-Bayesian estimation of the reliability derived from Binomial distribution

This paper introduces a new parameter estimation method, named E-Bayesian estimation method, to estimate reliability derived from Binomial distribution. The definition of E-Bayesian estimation of the reliability is proposed, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation of the reliability are also provided. Finally, it is shown, through a numerical example, that the new method is much simpler than hierarchical Bayesian estimation in practice.     

Fuzzy confidence interval for pH titration curve

In this paper we present a new method of confidence interval identification for Takagi–Sugeno fuzzy models in the case of the data with regionally changeable variance. The method combines a fuzzy identification methodology with some ideas from applied statistics. The idea is to find, on a finite set of measured data, the confidence interval defined by the lower and upper bounds. The confidence interval which defines the band that contains the measurement values with certain confidence. The method can be used when describing a family of uncertain nonlinear functions or when the systems with uncertain physical parameters are observed. In our example the proposed method is applied to model the pH-titration curve.     

Weighted Empirical Likelihood Ratio Confidence Intervals for the Mean with Censored Data

We propose a procedure to construct the empirical likelihood ratio confidence interval for the mean using a resampling method. This approach leads to the definition of a likelihood function for censored data, called weighted empirical likelihood function. With the second order expansion of the log likelihood ratio, a weighted empirical likelihood ratio confidence interval for the mean is proposed and shown by simulation studies to have comparable coverage accuracy to alternative methods, including the nonparametric bootstrap-t. The procedures proposed here apply in a unified way to different types of censored data, such as right censored data, doubly censored data and interval censored data, and computationally more efficient than the bootstrap-t method. An example of a set of doubly censored breast cancer data is presented with the application of our methods.     

基于灰色模型和Bootstrap理论的大规模定制质量控制方法研究

针对大规模定制生产中样本量小而无法直接应用传统控制图判断过程状态的问题,提出基于灰色模型和Bootstrap理论的质量控制方法.首先采用灰色模型,以现有样本为基础进行数据分析,适当扩展样本量;然后基于Bootstrap统计推断方法获得统计量的经验分布;最后建立样本均值和极差控制图,对生产过程的状态进行分析判断.研究表明,新方法可用于大规模定制生产尤其是新型号生产初期的质量预测和控制.     

Classroom note: Corrections to a well-known proposition concerning the two-dimensional density function

The purpose of this article is to bring attention to an error in a well-known proposition concerning the two-dimensional density function, which appears in several intermediate textbooks on probability and statistics. A counterexample is presented, and two corrected versions of the proposition are suggested.     

两个和K个分布函数相等的自助法检验(英文)

两个和Ｋ 个分布函数相等的检验在统计领域中,长期以来一直受到关注．为了克服高维空间中数据点的稀疏性,并且对一般情况进行处理,我们提出了几个投影追踪类型的统计量,并得到了这些统计量的极限分布的一些结果．对一些自助法逼近的性质进行了研究．更进一步地,由于计算的原因,对统计量的逼近,我们采用了数论方法,并进行了一些模拟试验     

Comparison of ‘Tail Method’ Exact Confidence Limits for the Difference of Binomial Probabilities

Suppose that Y ₁ and Y ₂ are independent and have Binomial(n ₁,p ₁) and Binomial (n ₂,p ₂) distributions respectively. Also suppose that θ=p ₁−p ₂ is the parameter of interest. We consider the problem of finding an exact confidence limit (either upper or lower) for θ. The solution to this problem is very important for statistical practice in the health and life sciences. The ‘tail method’ provides a solution to this problem. This method finds the exact confidence limit by exact inversion of a hypothesis test based on a specified test statistic. Buehler (J. Am. Stat. Assoc. 52, 482–493, 1957) described, for the first time, a finite-sample optimality property of this confidence limit. Consequently, this confidence limit is sometimes called a Buehler confidence limit. An early tail method confidence limit for θ was described by Santner and Snell (J. Am. Stat. Assoc. 75, 386–394, 1980) who used the maximum likelihood estimator of θ as the test statistic. This confidence limit is known to be very inefficient (see e.g. Cytel Software, StatXact, version 6, vol. 2, 2004). The efficiency of the confidence limit resulting from the tail method depends greatly on the test statistic on which it is based. We use the results of Kabaila (Stat. Probab. Lett. 52, 145–154, 2001) and Kabaila and Lloyd (Aust. New Zealand J. Stat. 46, 463–469, 2004, J. Stat. Plan. Inference 136, 3145–3155, 2006) to provide a detailed explanation for the dependence of this efficiency on the test statistic. We consider test statistics that are estimators, Z-statistics and approximate upper confidence limits. This explanation is used to find the situations in which the tail method exact confidence limits based on test statistics that are estimators or Z-statistics are least efficient.     

Lexicographic orientation and representation algorithms for comparability graphs,proper circular arc graphs,and proper interval graphs

We introduce a simple new technique which allows us to solve several problems that can be formulated as seeking a suitable orientation of a given undirected graph. In particular, we use this technique to recognize and transitively orient comparability graphs, to recognize and represent proper circular arc graphs, and to recognize and represent proper interval graphs. As a consequence, we derive and represent proper interval graphs. As a consequence, we derive simple new proofs of a theorem of Ghouila-Houri and a theorem of Skrien. Our algorithms are conceptually simpler than (and often of comparable efficiency to) the existing algorithms for these problems. © 1995 John Wiley & Sons, Inc.     

基于投影偏度和投影峰度的投影寻踪自助法的正态性检验

本文研究了多元分布的正态性检验问题,用投影寻踪自助法,获得了投影偏度和投影峰度正态性检验统计量,证明了在零假设成立时,所提出的偏度和峰度检验统计量的极限分布为一高斯过程的上界.为计算机模拟计算提供了有力的手段和依据.