多元分布下单边备择假设的两步检验

x~2检验是熟知的拟合优度检验.它适用于任意的备择假设,尤其是适用于一般的备择假设"H_0不真"的情况.但是,当备择假设是一个单边假设时,x~2检验没有用到单边假设所提供的信息.因此,一个充分利用单边备择假设信息的检验是有可能优于传统的x~2检验的.本文就是利用单边备择假设的信息给出了一个两步检验,并通过一个例子,详细介绍了两步检验法的实施,说明了其应用.     

犯两类错误概率相等的检验函数

设有总体X具有概率密度或概率分布列f(x,θ),θ未知,θ∈(?)={θ_0,θ_1},要检验假设(?),样本X_1,X_2、…、X_n 本文为克服最优势检验中原假设与备择假设地位不对称的矛盾,提出了一种检验法则:此检验函数具有与最优势检验形式相同的检验函数,且犯第一、第二两类错误的概率相等。本文证明了这样的检验验函数是存在的,并且举例以说明之。     

探讨提高高速公路路面质量的改进方案

采用偏度、峰度检验法检验数据分布,利用Pearson相关性分析,多元线性回归分析方法,判断4个高速公路路面质量指标的线性关系.对岩石类型分类,采用典型相关性分析法,建立了影响高速公路路面质量最重要和比较重要因素之间较精确的数学模型.通过合理的假设和简化,借鉴"开普勒猜想"问题,得出不同沙石球体半径与%Gmm(最大)之间的关系.将石料,沥青自由组合,采用秩和检验法检验不同组合对不同指标值的差异程度.     

线性模型中M检验原假设分布的随机加权逼近

在线性模型中M-方法可以用于线性假设检验, 其中M检验、Wald检验和Rao的计分型检验是最常用的检验准则. 但是在计算这些检验的临界值时都涉及到未知参数的估计. 在本文中我们利用随机加权的方法来逼近这些检验的原假设分布. 结果表明在原假设和局部对立假设之下随机加权统计量的渐近分布与原检验统计量在原假设之下的渐近分布相同. 因此我们不需要对冗余参数进行估计,利用随机加权的方法就可以得到这些检验的临界值. 而且在局部对立假设之下可以实现对功效的计算. 当取不同的误差分布和不同的随机权时, 我们对本文的方法进行了蒙特卡洛模拟. 结果表明用随机加权方法来逼近原假设分布是非常精确的.     

非正态情形下过程能力指数的近似置信限

文章讨论了当过程不满足正态性假设的情形下过程能力指数的近似置信限,并以Weibull分布为例给出了指数C′_(pm)的近似置信区间的具体形式和假设检验的检验统计量。最后给出了模拟验证。     

关于假设检验的一点注记

在假设检验的过程中,对一个参数的检验法一般来说是不唯一的.对于正态总体,当均值已知,而就方差进行检验时,若能选用自由度为n的χ2统计量,则其为无偏检验,而且为一定标准下的最佳检验.     

统计学入门(Ⅸ)

十八、对正态总体均值和方差的检验 在这一节中我们将具体列出关于一个正态总体的均值μ或方差σ2的假设检验.根据上节的讨论,这些检验与μ或σ2的置信区间的构造有关.因此我们不准备详细地给出这些检验的推导过程,仅将结果以表格形式列出,并给出若干说明性的例子.18-1关于均值u的假设检验 需要检验的假设H0:μ=μ0(双侧检验);μ≥μ0或μ≤μ0(单侧检验),其中μ0是已知的常数.检验统计量当σ已知时用当σ未知时用 例18-1炼钢厂为测定温铁炉铁水温度,用测温枪(主要装置为一种热电偶)测温6次,记录如下(单位℃): 1318, 1315, 1308, 1316, 131…     

上界型拟合优度检验

对简单零假设情况,构造出一类上界型拟合优度检验.取不同的参数λ和不同的权函数,这类检验不仅包含许多已存在的检验,如Kolmogorov-Smirov检验,Berk-Jones检验等,而且还给出一些新的检验.众所周知,对不同的问题,"最优"的检验是不同的,有必要对这类检验的性质进行讨论.该文对任意给定的λ和较一般的权函数q(·),在较弱的条件下,导出了相应上界型检验统计量在零假设下的渐近分布,研究了它们的局部渐近功效;在若干固定备择假设下,对该类检验的功效进行了模拟研究.模拟结果表明,在不同的备择假设下,功效较优的检验是不同的,不存在对所有情况一致最优的检验.     

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.     

平滑转换向量误差修正模型的非线性协整SupLM检验

本文考虑平滑转换向量误差修正模型的非线性协整检验问题,相对于传统的两步检验法,给出已知协整向量下的直接检验非线性协整的SupLM检验方法,通过定义平滑转换协整模型,给出SupLM检验统计量,在原假设下得到检验统计量的渐近分布和相关的bootstrap算法,模拟结果和实例计算表明了该方法的有效性。     

Exact two-sample nonparametric test for quantile difference between two populations based on ranked set samples

Creation of a ranked set sample, by its nature, involves judgment ranking error within set units. This ranking error usually distorts statistical inference of the population characteristics. Tests may have inflated sizes, confidence intervals may have incorrect coverage probabilities, and the estimators may become biased. In this paper, we develop an exact two-sample nonparametric test for quantile shift between two populations based on ranked set samples. This test is based on two independent exact confidence intervals for the quantile of interest corresponding to the two populations and rejects the null hypothesis of equal quantiles if these intervals are disjoint. It is shown that a pair of 83 and 93% confidence intervals provide a 5 and 1% test for the equality of quantiles. The proposed test is calibrated for the effect of judgment ranking error so that the test has the correct size even under a wide range of judgment ranking errors. A small scale simulation study suggests that the test performs quite well for cycle sizes as small as 2.     

A Nonparametric Test for the Equivalence of Populations Based on a Measure of Proximity of Samples

We propose a new measure of proximity of samples based on confidence limits for the bulk of a population constructed using order statistics. For this measure of proximity, we compute approximate confidence limits corresponding to a given significance level in the cases where the null hypothesis on the equality of hypothetical distribution functions may or may not be true. We compare this measure of proximity with the Kolmogorov–Smirnov and Wilcoxon statistics for samples from various populations. On the basis of the proposed measure of proximity, we construct a statistical test for testing the hypothesis on the equality of hypothetical distribution functions.     

线性度量误差模型的序列相关检验

回归模型的序列相关检验是经济和金融数据分析中的一项重要的工作.基于最小二乘残差,作者提出了一个检验统计量以检验线性度量误差模型的误差序列是否存在序列相关性.在零假设下,得到了检验统计量的渐近分布.数值模拟结果表明,这里提出的检验统计量具有良好的有限样本性质.     

非等定时截尾寿命试验方案指数分布情形平均寿命的置信限

非等定时截尾寿命试验方案是价值高或制造复杂的产品在实际试验中常常采用的方案 ,本文在此方案下给出一种关于指数分布平均寿命的置信限的解决方案。这个置信限在有一定意义下是最优的 ,并且是不保守的。     

Asymptotic optimality of multivariate linear hypothesis tests

The optimal exponential rate at which the Type II error probability of a multivariate linear hypothesis test can tend to zero while the Type I error probability is held fixed is given. The likelihood ratio test, the test of Hotelling and Lawley, the test of Bartlett, Nanda, and Pillai, and the test of Roy are shown to be asymptotically optimal in the sense that for each of these tests the exponential rate of convergence of the type II error probability attains the optimal value. Some other tests for the multivariate linear hypothesis are shown not to be asymptotically optimal.     

成败型元件串并联系统及并串联系统可靠性置信下限近似解的讨论

本文讨论由相互独立的成败型元件组成的串并联系统及并串联系统可靠性置信下限的近似解。本文利用系统诸元件的试验数据,在一、二阶矩拟合的原则下将其折合为原系统的伪试验数及伪成功数,然后利用单个成败型元件的可靠性的经典精确置信下限作为原系统可靠性置信下限的近似值。本文推导了伪试验数N及伪成功数S的计算公式,并给出了计算实例。     

Tests on categorical data from the unionintersection principle

Summary The union-intersection principle developed by S. N. Roy [13] has become an important tool in multivariate analysis. In this paper the union-intersection principle is applied to obtain some of the standard tests of hypothesis on categorical data, as well as a new test for homogeneity in anr×c table. In particular, tests of hypothesis on a single multinomial distribution and tests for the comparison of two multinomials are derived on the union-intersection principle and the corresponding simultaneous confidence intervals obtained. A test for homogeneity in anr×c table is derived on the union-intersection principle, and for the case of equal sample size from each of ther populations it is shown that the test statistic is distributed as the largest root of a central Wishart matrix.     

Simultaneous confidence band and hypothesis test in generalised varying-coefficient models

Generalised varying-coefficient models (GVC) are very important models. There are a considerable number of literature addressing these models. However, most of the existing literature are devoted to the estimation procedure. In this paper, we systematically investigate the statistical inference for GVC, which includes confidence band as well as hypothesis test. We establish the asymptotic distribution of the maximum discrepancy between the estimated functional coefficient and the true functional coefficient. We compare different approaches for the construction of confidence band and hypothesis test. Finally, the proposed statistical inference methods are used to analyse the data from China about contraceptive use there, which leads to some interesting findings.     

基于ZIP模型的零膨胀检验方法的比较研究

针对已存在关于零膨胀的R检验、C检验、Score检验、卡方检验、似然比检验、Wald检验和基于置信区间检验,通过Monte Carlo模拟分析方法,在功效和犯第一类错误比例的意义下,在不同零膨胀程度、不同均值和不同样本量下对上述检验作比较研究.得到了不同条件下7种检验方法的优良性,并结合理论对7种检验方法进行分析.