二项选择敏感性问题调查的基本方法——敏感性问题调查方法(Ⅰ)

二项选择敏感性问题调查的基本方法．本讲座介绍敏感性问题调查的随机化回答技术（ＲＲＴ）,本文首先介绍二项选择问题的基本方法：沃纳模型,西蒙斯模型     

线性混合模型中方差分量的广义推断

本文考虑了线性混合模型中方差分量的假设检验和区间估计问题.基于广义P-值和广义置信区间的概念,构造了对应于随机效应的单个方差分量的精确检验和置信区间.所构造的广义p-值和广义置信区间是最小充分统计量的函数.对于两个独立线性混合模型中对应于随机效应的方差分量的比较,建立了精确检验和置信区间.进-步,研究了所给检验和置信区间的统计性质,给出了这些检验方法与文献中已有方法的功效比较的模拟结果.模拟结果表明,新检验在功效方面有显著的改进.最后,通过-个实例来演示本文方怯.     

广义空间模型的方差齐性检验

研究了广义空间模型的方差齐性检验问题,在异方差情形下导出了Score检验统计量的具体形式和近似分布.分别应用于混合空间自回归模型和空间误差模型,给出了相应的检验统计量和渐近分布.并利用Monte Carlo模拟对检验统计量的性质进行分析.最后,通过中国能源利用效率的区域特征数据证明了方法的有效性.     

随机化回答模型中的贝叶斯方法

本文将贝叶斯方法应用到敏感性问题中的随机化回答调查法中,讨论了西蒙斯的一个样本的无关问题模型中的贝叶斯估计和最大后验估计,并给出了这两种估计的一种近似算法．     

纵向数据半参数混合效应模型中的估计方法

本文将Tao等(1999)提出的线性混合效应模型推广为半参数混合效应模型,给出了模型参数、回归函数和随机效应密度的估计,并研究了估计的渐近性质.统计模拟表明我们给出的估计方法是可行的.     

广义Pareto分布变点检测似然比模型

为检测极端事件的状态变化,基于似然比方法研究了广义Pareto分布(Generalized Pareto Distribution,GPD)变点检测模型.考虑三参数GPD变点的检验问题,提出了最大似然比检验统计量.通过证明参数变换后GPD的对数似然和检验统计量的一系列极限性质,得到了检验统计量的渐近分布.通过模拟研究,对该方法的有限样本性质进行了评价,实例分析也验证了该方法的可行性.     

离散型广义非线性纵向数据模型中偏离名义离差的检验及其功效模拟

离散型广义非线性模型包括Poisson,二项,负二项模型.本文讨论离散型广义非线性纵向数据模型中偏离名义离差的检验问题,得到了检验的score统计量,并利用MonteCarlo方法研究了检验统计量的性质.最后,利用杀虫剂数据说明了检验方法的应用.     

泊松回归模型中协变量含误差的经验似然推断

在模型的协变量含有测量误差的情况下,考虑一类泊松回归模型的统计推断问题.通过巧妙地构造辅助随机向量,提出一个工具变量类型的经验似然统计推断方法.证明构造的经验对数似然比函数渐近服从标准卡方分布,进而给出了回归系数的置信区间.所提出的估计方法可以有效地消除测量误差对估计精度的影响,并且具有较好的有限样本性质.     

频率源噪声的时域特性分析

针对频率源的5种噪声,建立了一种新的时域模型——动态模型.以此模型为基础并结合“降阶-积分”方法,首次推导出了全部5种噪声在相位上的自相关函数,得到了比Allan方差更为广泛、更为一般的时域噪声特性.作为一个结果,本文还给出相位噪声3个常用统计量的统计性质.     

基于云模型的模糊综合评价方法及应用

阐述了利用正态云模型代替模糊隶属函数进行模糊综合评价的方法.运用云模型的逆向云发生器、云运算原理,结合云模型的模糊性、随机性、统计性性质对一个评价系统进行综合评价.最后使用食品安全监管检测数据分析比对了基于云模型的模糊综合评价方法与常规模糊综合评价方法,算例表明云模型的模糊评价方法具有模糊隶属函数方法所不具备的优势.     

关于Simmons模型的几点讨论

本文介绍了Simmons模型的参数选择方法 ,并对几种Simmons模型的精度、合作程度进行了比较 ,最后推荐一种新的随机化装置 ,不仅在精度上有所提高 ,而且操作简便 ,提高了被访者的合作程度     

Geometric secret sharing schemes and their duals

Given a set of participants we wish to distribute information relating to a secret in such a way that only specified groups of participants can reconstruct the secret. We consider here a special class of such schemes that can be described in terms of finite geometries as first proposed by Simmons. We formalize the Simmons model and show that given a geometric scheme for a particular access structure it is possible to find another geometric scheme whose access structure is the dual of the original scheme, and which has the same average and worst-case information rates as the original scheme. In particular this shows that if an ideal geometric scheme exists then an ideal geometric scheme exists for the dual access structure.This work was supported by the Science and Engineering Research Council Grant GR/G 03359.This work was supported by the Australian Research Council.     

P-algorithm based on a simplicial statistical model of multimodal functions

A well-recognized one-dimensional global optimization method is generalized to the multidimensional case. The generalization is based on a multidimensional statistical model of multimodal functions constructed by generalizing computationally favorable properties of a popular one-dimensional model—the Wiener process. A simplicial partition of a feasible region is essential for the construction of the model. The basic idea of the proposed method is to search where improvements of the objective function are most probable; a probability of improvement is evaluated with respect to the statistical model. Some results of computational experiments are presented.     

Some properties of projectors associated with the WLSE under a general linear model

Projectors associated with a particular estimator in a general linear model play an important role in characterizing statistical properties of the estimator. A variety of new properties were derived on projectors associated with the weighted least-squares estimator (WLSE). These properties include maximal and minimal possible ranks, rank invariance, uniqueness, idempotency, and other equalities involving the projectors. Applications of these properties were also suggested. Proofs of the main theorems demonstrate how to use the matrix rank method for deriving various equalities involving the projectors under the general linear model.     

基于反馈回归法的用电量预测模型研究

多元线性回归法是用电量预测中常用的一种方法,带反馈的多元线性回归法是一种改进的回归方法,具有更高的精度.本文在此基础上进行了多次反馈,即利用带多次反馈的多元线性回归法,结合SPSS软件进行统计分析,并以陕西省用电量为例探究分析多次反馈的多元线性回归法在用电量预测中的应用,从而得到更精准的用电量预测模型.最后以四川省的用电量数据对模型进行了验证,体现出了该模型的优越之处.     

Compound nonlinear congruential pseudorandom numbers

The nonlinear congruential method for generating uniform pseudorandom numbers has several very promising properties. However, an implementation in multiprecision of these pseudorandom number generators is usually necessary. In the present paper a compound version of the nonlinear congruential method is introduced, which overcomes this disadvantage. It is shown that the generated sequences have very attractive statistical independence properties. The results that are established are essentially best possible and show that the generated pseudorandom numbers model true random numbers very closely. The method of proof relies heavily on a thorough analysis of exponential sums.     

汽车千车故障数的预测与分析

针对原有千车故障数统计方法上的不足,本文从改进统计方法着手,提出一种新的统计方法即重新定义千车故障数,然后利用数据挖掘中的聚类分析方法将具有相同特征的批次综合起来考虑,建立通用的运筹模型.针对缺失数据、近期预测这两个问题,本文对通用模型进行调整,“学习”出同类数据间的不同权值,然后利用加权数据,并通过拟合曲线来求出预测值.由于远期预测中数据的严重缺乏,则是从纯粹统计学的角度出发,计算得到预测值.预测模型通用性强,适用面较广.本文应用了SAS和MATLAB两种软件来求解上述模型,预测结果准确率较高,并且符合实际情况.     

A Proof of Simmons' Conjecture

An open problem posed by Simmons is whether two given permutations of the vertices of the deBruijn graph have the same cycle structure, or not. We present a solution to this problem and find the complete cycle structure.     

Study and modelling of two apple quality attributes: the soluble solids content and the firmness

Recently, the basic dynamics of fruit characteristics have been modelled using a stochastic approach. The time evolution of apple quality attributes was represented by means of a system of differential equations in which the initial conditions and model parameters are both random. In this work, a complete study of two apple quality attributes, the soluble solids content and the firmness, is carried out. For each of these characteristics, the system of differential equations is linear and the state variables and the parameters are represented as random variables with their statistical properties (mean values, variances, covariances, joint probability density function) known at the initial time. The dynamic behaviour of these statistical properties is analysed. The variance propagation algorithm is used to obtain an analytical expression of the dynamic behaviour of the mean value, the variance, the covariance and the probability density function. A Monte Carlo method and the Latin hypercube method were developed to obtain a numerical expression of the dynamic behaviour of these statistical quantities and particularly to follow the time evolution of joint probability density function which represents one but the best mean to characterize random phenomena linked with fruit quality attributes.