参数法和非参数法估计组合样中被测组分含量的置信区间

本文以散装生铁块的随机样本分析结果为基础,应用Ｍｏｎｔｅ Ｃａｒｌｏ模拟法考察了组合样本中Ｓｉ、Ｍｎ,Ｃ,Ｓ,Ｐ含量（或份样平均值）的分布情况,研究了组分含量的置信区间,对参数法和非参数法的结果进行了比较。结果表明,对近似符合正态分布的原始总体或当组合样中的份样数目较多时,两种方法所估计的置信区间相近。但对偏离正态分布（或ｔ－分布）的总体且组合样中的份样数目较少时,非参数法较参数法的结果更符合实际     

三棱镜折射率测量结果的不确定度评定

根据不确定度的有关概念及具体实验教学模型 ,提出了测量不确定度的简化模式. 结合分光计 测三棱镜折射率的例子 ,进行了具体分析 ,给出了其测量不确定度的最终评定.     

Evaluating Lipschitz Constants for Functions Given by Algorithms

This paper describes an efficient method (O(n)) to evaluate the Lipschitz constant for functions described in some algorithmic language. Considering arithmetical operations as the basis of the algorithmic language and supported by control structures, the rules to evaluate such Lipschitz constants are presented and their correctness is proved. An extension of the method to evaluate Lipschitz constants over interval domains is also presented. Examples are presented, but the effectiveness of the method is doubtful when compared to other approaches, and effective enhancements based on slope evaluations are also explored.     

Admissibility of Confidence Estimators in the Regression Model

In the regression model, we assume that the independent variables are random instead of fixed. Consider the problem of estimating the coverage function of a usual confidence interval for the unknown intercept parameter. In this paper, we consider a case in which the number of unknown parameters is smaller than 5. We show that the usual constant coverage probability estimator is admissible in the usual sense in this case. Note that this estimator is inadmissible in the usual sense in the other case where the number of unknown parameters is greater than 4.     

巴斯卡分布参数p的置信区间

讨论了巴斯卡分布与Beta分布的联系,并通过F分布的分位点给出了参数p的置信水平为1-α的置信区间.     

Panel模型中的精确检验和置信区间

利用广义p-值和广义置信区间的概念,研究了Panel模型中未知参数的检验和置信区间问题.对于回归系数,分别考虑了单个情形和多个线性无关情形下的检验和置信区间问题,得到了精确检验和置信区间.对于方差分量,研究了其任意线性组合的检验和置信区间问题,建立了精确检验和置信区间.基于广义p-值和广义置信区间,获取精确检验和置信区间的方法具有计算方便、易应用于小样本问题的特点.最后,分别从理论和数值上研究了这些精确检验和置信区间的统计性质.     

Consensus,Polarization and Hysteresis in the Three-State Noisy q-Voter Model with Bounded Confidence

In this work, we address the question of the role of the influence of group size on the emergence of various collective social phenomena, such as consensus, polarization and social hysteresis. To answer this question, we study the three-state noisy q-voter model with bounded confidence, in which agents can be in one of three states: two extremes (leftist and rightist) and centrist. We study the model on a complete graph within the mean-field approach and show that, depending on the size q of the influence group, saddle-node bifurcation cascades of different length appear and different collective phenomena are possible. In particular, for all values of q>1, social hysteresis is observed. Furthermore, for small values of q∈(1,4), disagreement, polarization and domination of centrists (a consensus understood as the general agreement, not unanimity) can be achieved but not the domination of extremists. The latter is possible only for larger groups of influence. Finally, by comparing our model to others, we discuss how a small change in the rules at the microscopic level can dramatically change the macroscopic behavior of the model.     

系统可靠度置信下限估计方法及其应用

针对寿命服从指数分布的随机截尾样本,研究单元及系统可靠度的评估方法,给出了系统可靠度置信下限估计方法,该方法同样适用于工程中常见的定时截尾样本与定数截尾样本的系统可靠度评估问题。首先通过分位数填充算法将随机截尾数据补充成虚拟完全样本,然后基于信仰推断,给出系统内每个单元失效率的信仰分布,最后根据指数分布的特点,从失效率角度出发,采用蒙特卡罗法对单元失效率进行随机抽样,结合系统可靠性模型得到系统失效率的分布,在给定置信水平下即可得到系统失效率上限,进而得到工程上特别关注的系统可靠度置信下限。     

n维球内均匀分布的参数估计

研究了n维球内均匀分布的参数的点估计与区间估计,利用次序统计量得到了球半径的最大似然估计,在此基础上构造了球半径的无偏估计,并且证明了该无偏估计的相合性.利用构造枢轴量的方法得到了球半径的最短置信区间.     

Aspects of Frequentism

Some aspects of the Frequentist approach to statistical data analysis are presented and discussed. The construction of confidence intervals for parameters is explained and made concrete with a detailed example. The intervals correspond to parameter ranges where the observed data is in a ‘favored’ part of the expected results distribution. Goodness‐of‐fit tests are defined similarly; here, a Bayesian argument is given for the usefulness of these tests. The possible over‐interpretation of Frequentist results is also discussed.