位置刻度分布族中参数的两步置信区间

寻找一些分布中的参数的具有预先给定宽度和预先给定覆盖概率的置信区间是令人感兴趣的，对于位置刻度分布族中位置参数和刻度参数，这种类型的置信区间的存在性问题已在文献中被解决，本文利用两步抽样，具体地构造出这样的固定宽度置信区间，此外，对于Cauchy分布，第一阶段的最优抽样量和一些统计量的分位点也被计算出，所得到的结果具有应用价值。     

The effect of project-based learning on students’ statistical literacy levels for data representation

The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students’ statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35 in the experimental group and 35 in the control group, took this test twice, one before the application and one after the application. All the raw scores were turned into linear points by using the Winsteps 3.72 modelling program that makes the Rasch analysis and t-tests, and an ANCOVA analysis was carried out with the linear points. Depending on the findings, it was concluded that the project-based learning approach increases students’ level of statistical literacy for data representation. Students’ levels of statistical literacy before and after the application were shown through the obtained person-item maps.     

正态总体中方差的两步置信区间

利用两阶段抽样，我们具体给出了正态总体方差的一个置信区间，它同时满足可靠度与精度。利用数值计算的方法，我们计算出第一阶段的最优抽样量。此外，我们证明了一次抽样时同时满足可靠度与精度的置信区间的不存在性。     

Exact meta-analysis of several independent progressively type-II censored data

Exact inference for the case when multiple independent progressively Type-II censored samples are pooled is considered. Two representations for the marginal distributions of the resulting pooled order statistics are given, a direct method and an iterative method. The coverage probabilities and expected widths of exact nonparametric confidence intervals for quantiles are compared for various scenarios with one or more independent samples.     

置信区间的随机加权估计

用随机加权法建立了分位点ｑ的置信区间，又用后向临界点导出了更实用的置信区间。导出的置信区间是非参数的且和原置信区间长度相同。     

Empirical likelihood-based dimension reduction inference for linear error-in-responses models with validation study

In this paper, linear errors-in-response models are considered in the presence of validation data on the responses. A semiparametric dimension reduction technique is employed to define an estimator of β with asymptotic normality, the estimated empirical loglikelihoods and the adjusted empirical loglikelihoods for the vector of regression coefficients and linear combinations of the regression coefficients, respectively. The estimated empirical log-likelihoods are shown to be asymptotically distributed as weighted sums of independent x12 and the adjusted empirical loglikelihoods are proved to be asymptotically distributed as standard chi-squares, respectively.     

When not to analyze data: Decision making on missing responses in dual scaling

In exploratory data analysis, handling of missing responses requires special considerations because of the absence of a model for them. This study investigates effects of missing responses on dual scaling results, in particular a practical decision rule when to and not to impute for missing responses. More specifically, three questions are asked: when to discard a subject, when to exclude a variable, and when to stop data analysis entirely. The decision rule is based on the concept of substantial discrepancy in the scaling outcome between the best and worst imputations for missing responses. This problem is discussed in the context of the current knowledge on missing responses in data analysis.     

Bootstrapping the mode

The problem of constructing bootstrap confidence intervals for the mode of a density is considered. Estimates of the mode are derived from kernel density estimates based on fixed and data-dependent bandwidths. The asymptotic validity of bootstrap techniques to estimate the sampling distribution of the estimates is investigated. In summary, the results are negative in the sense that a straightforward application of a naive bootstrap yields invalid inferences. In particular, the bootstrap fails if resampling is done from the kernel density estimate. On the other hand, if one resamples from a smoother kernel density estimate (which is necessarily different from the one which yields the original estimate of the mode), the bootstrap is consistent. The bootstrap also fails if resampling is done from the empirical distribution, unless the choice of bandwidth is suboptimal. Similar results hold when applying bootstrap techniques to other functionals of a density.     

混合线性模型中方差比的置信区间

本文利用信仰推断给出了求混合线性模型中方差比的置信区间的方法，结果表明所得区间估计具有不变性。另外，本文给出了两种求区间估计的近似方法。     

统计模拟

本文概述了统计模拟问题,介绍了统计量分布函数模拟,大样本模拟,检验功效模拟,经济模拟及优化问题模拟等,给出了一些模拟实例。     

随机套分类模型中方差分量区间估计的改进

首先给出了随机套分类模型中方差分量基于由方差分析产生的平方和的区间估计.然后以此为基础进行了改进,推导出了同时依赖于均值与平方和的区间估计.二者的区间长度相同,但后者有较高的置信度.     

基于置信分布的多个对数正态总体的公共均值的置信区间的构建（英文）

在实际应用中需要拟合正的偏态数据时,对数正态分布是通常的选择.当通过多重比较确定了多个对数正态分布总体的均值相同时,如何能够利用更多的信息,同时使用这些对数正态分布总体的信息来构建公共均值的置信区间成为了众多学者颇为关注的问题.本篇文章提出了一种新的基于置信分布的方法来构建多个对数正态总体公共均值的置信区间,该方法通过对相关量的样本方差进行加权来提高效率.进而对文中提出的基于置信分布的置信区间的构建方法进行了蒙特卡洛模拟研究,模拟结果表明,我们提出的构建方法可以得到很好的覆盖概率和较短的区间宽度.文章的最后用三个实际数据来验证了文中所提出方法的表现.     

Determination of sample sizes for setting β-content tolerance limits controlling both tails of the normal distribution

The problem of determining sample size for two-sided-β-content tolerance intervals which control both tails of the normal distribution is investigated. The tolerance limits are defined to assure that the tail proportions do not exceed specified values p₁ and p₂. We determine the minimum sample size so that, at a given confidence level, the tail proportions will not be too small, i.e., so that the tolerance interval will not be overly conservative. Tables of the sample size n and the corresponding factors are provided.     

The Local Bootstrap for Kernel Estimators under General Dependence Conditions

We consider the problem of estimating the distribution of a nonparametric (kernel) estimator of the conditional expectation g(x; ) = E((X _t+1) | Y _t,m = x) of a strictly stationary stochastic process {X _t , t 1}. In this notation (·) is a real-valued Borel function and Y _t,m a segment of lagged values, i.e., Y_t,m=(X_{t-i 1},X_{t-i 2},...,X_{t-i m}), where the integers i _i , satisfy 0 i₁2...m>. We show that under a fairly weak set of conditions on {X _t , t 1}, an appropriately designed and simple bootstrap procedure that correctly imitates the conditional distribution of X _t+1 given the selective past Y _t,m , approximates correctly the distribution of the class of nonparametric estimators considered. The procedure proposed is entirely nonparametric, its main dependence assumption refers to a strongly mixing process with a polynomial decrease of the mixing rate and it is not based on any particular assumptions on the model structure generating the observations.     

均匀分布参数的最短置信区间

将求均匀分布未知参数的最短置信区间转化为条件极值问题,给出了均匀分布参数的最短置信区间,推广了原有的结论.     

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The log-normal distribution is a common choice for modeling positively skewed data arising from many practical applications.This article introduces a new method of constructing confidence interval for a common mean shared by several log-normal populations through confidence distributions, which combines all information from independent sources. We develop a non-trivial weighting approach by taking account of the sample variances of related quantities to enhance efficiency. Combined confidence distributions are used to construct confidence intervals for the common mean and a simplified version of one existing method is also proposed. We conduct simulation studies to evaluate the performance of the proposed methods in comparison with existing methods. Our simulation results show that the weighting approach yields shorter interval length than the non-weighting approach. The newly proposed confidence intervals perform very well in terms of empirical coverage probability and average interval length. Finally, applications of the proposed methodology is illustrated through three real data examples.     

有序处理连续比较的置信区间

为有序均值的连续比较提出了一个新的检验过程.他们的过程对满足简单序的均值有重要的应用价值,例如在研究增长剂量对药物效用的影响. 与其它检验过程相比(例:Hayterucite{4}中的检验), 其优点在于产生了更短的连续比较的置信限,从而能够提供更多机会发现在何药剂量处有不同的效用.但作为有序均值的齐性检验, 它的势表现远劣于其它检验.本文的目的是提出一检验过程在尽量保持Lee andSpurrierucite{8}检验的优点的同时大大地提高其势表现.