The asymptotic validity of invariant procedures for the repeated measures model and multivariate linear model

Fairly general sufficient conditions are given to guarantee that invariant tests about means in the multivariate linear model and the repeated measures model have the correct asymptotic size when the normal assumption under which the tests are derived is relaxed. These conditions are the same as Huber's condition which guarantees asymptotic validity of the size of the F-test for the univariate linear model.     

Tests for simultaneously determining numbers of clusters and their shape with multivariate data

Given a set of data, very little is known about tests to determine number of clusters and/or elements of the clusters. Even in the simplest case of detecting between only one or two clusters with multivariate normal data, theoretically the number of tests needed seems to be infinite. Alternatively, suppose N independent estimates of generalized variances (GVs) are computed from a given set of p-dimensional vector observations. Assuming multivariate normality, tests based on GVs are proposed which objectively and uniquely determine, simultaneously, the number of clusters and their corresponding elements. Only a reasonably small nunber of tests are required for this stepwise procedure. The exact percentage points are either available from existing tables or can be computed from a result presented.     

AN ANALYSIS OF AMULTIVARIATE TWO－WAY MODEL WITH INTERACTION AND NO REPLICATION

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Nonnull distributions of two test criteria for independence under local alternatives

For testing the independence of q-sets in a p-variate normal population, the asymptotic distributions of the likelihood ratio test, and the test proposed by the author under local alternatives are derived in terms of noncentral χ² variates.     

Generalized model with repeated calls in case of extreme load

Recurrence formulas for finding any desired number of terms in the asymptotic expansion of basic stationary performance measures of a generalized full-available system with repeated calls into a power series of the intensity of primary calls as it tends to infinity are derived. The first 3–4 terms of the expansion are found in explicit form. Other coefficients can be found numerically. It is shown that a number of interesting particular cases can be obtained from the model by proper choice of the values of input parameters. Among them it is worth mentioning models with possibility of call repetitions because of unsuccessful finishing of waiting time, inner blocking or unsuccessful finishing of service time. This revised version was published online in June 2006 with corrections to the Cover Date.     

Independence of Likelihood Ratio Criteria for Homogeneity of Several Populations

Let _i be an i-tb population with a probability density function f(· | _i ) with one dimensional unknown parameter _i = 1, 2, ... , k. Let n _i sample be drawn from each _i . The likelihood ratio criteria _j|(j–1) for testing hypothesis that the first j parameters are equal against alternative hypothesis that the first (j – 1) parameters are equal and the j-th parameter is different with the previous ones are defined, j = 2, 3, ... , k. The paper shows the asymptotic independence of _j|(j–1)'s up to the order 1/n under a hypothesis of equality of k parameters, where n is a number of total samples.     

Higher order asymptotic theory for normalizing transformations of maximum likelihood estimators

Suppose thatX _n =(X ₁,...X _n) is a collection ofm-dimensional random vectorsX _i forming a stochastic process with a parameter . Let be the MLE of . We assume that a transformationA( ) of has thek-thorder Edgeworth expansion (k=2,3). IfA extinguishes the terms in the Edgeworth expansion up tok-th-order (k2), then we say thatA is thek-th-order normalizing transformation. In this paper, we elucidate thek-th-order asymptotics of the normalizing transformations. Some conditions forA to be thek-th-order normalizing transformation will be given. Our results are very general, and can be applied to the i.i.d. case, multivariate analysis and time series analysis. Finally, we also study thek-th-order asymptotics of a modified signed log likelihood ratio in terms of the Edgeworth approximation.Research supported by the Office of Naval Research Contract N00014-91-J-1020.     

Tests of elliptical symmetry and the asymptotic tail behavior of the statistics

In this paper, some test statistics Of Kolmogorov type and Cramervon Mises type based on projection pursuit technique are proposed for testing the sphericity problem of a high-dimensional distribution. The limiting distributions of the test statistics are derived under the null hypothesis. The asymptotic properties of Bootstrap approximation are investigated and the tail behaviors of the statistics are studied.     

Tests for the mean direction of the Langevin distribution with large concentration parameter

In this paper we study the asymptotic behaviors of the likelihood ratio criterion (T_L^(s)), Watson statistic (T_W^(s)) and Rao statistic (T_R^(s)) for testing H_0s: μ (a given subspace) against H_1s: μ , based on a sample of size n from a p-variate Langevin distribution M_p(μ, κ) when κ is large. For the case when κ is known, asymptotic expansions of the null and nonnull distributions of these statistics are obtained. It is shown that the powers of these statistics are coincident up to the order κ⁻¹. For the case when κ is unknown, it is shown that T_R^(s) T_L^(s) T_W^(s) in their powers up to the order κ⁻¹.     

Simultaneous optimal estimates of fixed effects and variance components in the mixed model

For a general linear mixed model with two variance components, a set of simple conditions is obtained, under which, (i) the least squares estimate of the fixed effects and the analysis of variance (ANOVA) estimates of variance components are proved to be uniformly minimum variance unbiased estimates simultaneously; (ii) the exact confidence intervals of the fixed effects and uniformly optimal unbiased tests on variance components are given; (iii) the exact probability expression of ANOVA estimates of variance components taking negative value is obtained.     

教师对教学质量影响程度的单因素方差分析

用单因素方差分析的方法,对同年级26个班级数学期终考试成绩进行分组分析,并得到结论,教师在教学过程中起主导作用,但教师不是影响教学质量的首要因素.     

Normal Linear Regression Models With Recursive Graphical Markov Structure

A multivariate normal statistical model defined by the Markov properties determined by an acyclic digraph admits a recursive factorization of its likelihood function (LF) into the product of conditional LFs, each factor having the form of a classical multivariate linear regression model (≡WMANOVA model). Here these models are extended in a natural way to normal linear regression models whose LFs continue to admit such recursive factorizations, from which maximum likelihood estimators and likelihood ratio (LR) test statistics can be derived by classical linear methods. The central distribution of the LR test statistic for testing one such multivariate normal linear regression model against another is derived, and the relation of these regression models to block-recursive normal linear systems is established. It is shown how a collection of nonnested dependent normal linear regression models (≡Wseemingly unrelated regressions) can be combined into a single multivariate normal linear regression model by imposing a parsimonious set of graphical Markov (≡Wconditional independence) restrictions.     

Testing some covariance structures under a growth curve model

This paper considers three types of problems: (i) the problem of independence of two sets, (ii) the problem of sphericity of the covariance matrix Σ, and (iii) the problem of intraclass model for the covariance matrix Σ, when the column vectors of X are independently distributed as multivariate normal with covariance matrix Σ and E(X) = BξA,A and B being given matrices and ξ and Σ being unknown. These problems are solved by the likelihood ratio test procedures under some restrictions on the models, and the null distributions of the test statistics are established.     

应用方差分析探讨影响电厂高速混床阻力大的主要因素

本文应用数理统计中的方差分析原理 ,对影响火力发电厂混床阻力大原因进行了数据分析和探讨 ,为改造设备、提高混床出水质量提供了可靠的论据。     

A study of redundancy of some variables in covariate discriminant analysis

The redundancy of some variables in discriminant analysis and its tests were developed by Rao (1946,Sankhyā,7, 407–414; 1948,Biometrika,35, 58–79, 1970,Essays in Probability and Statistics, (eds. R. C. Boseet al.), 587–602, Univ. of North Carolina Press, Chapel Hill), and were further studied by McKay (1977,J. Roy. Statist. Soc. Ser. B,39, 371–380) and Fujikoshi (1982,Ann. Inst. Statist. Math.,34, 523–530). These are now extended to the most general situation which includes redundancy in covariate as well as main variables in discrimination between two or more groups. The likelihood ratio test is derived in a closed form. An alternative test is also suggested.     

A new method of spectral decomposition of covariance matrix in mixed effects models and its applications

For the mixed effects models with balanced data, a new ordering of design matrices of random effects is defined, and then a simple formula of the spectral decomposition of covariance matrix is obtained. To compare with the two methods in literature, the decomposition can not only give the actual number of all distinct eigenvalues and their expression, but also show clearly the relationship between the design matrices of random effects and the decomposition. These results can be applied to the problems for testifying the analysis of the variance estimate being a minimum variance unbiased under all random effects models and some mixed effects models with balanced data, for finding the explicit solution of maximum likelihood equations for the general mixed effects model and for showing the relationship between the spectral decomposition estimate and the analysis of variance estimate.     

Stochastic volatility model and technical analysis of stock price

In the stock market, some popular technical analysis indicators (e.g. Bollinger Bands, RSI, ROC, ...) are widely used by traders. They use the daily (hourly, weekly, ...) stock prices as samples of certain statistics and use the observed relative frequency to show the validity of those well-known indicators. However, those samples are not independent, so the classical sample survey theory does not apply. In earlier research, we discussed the law of large numbers related to those observations when one assumes Black-Scholes’ stock price model. In this paper, we extend the above results to the more popular stochastic volatility model.     

Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model

This paper is concerned with the null distribution of test statistic T for testing a linear hypothesis in a linear model without assuming normal errors. The test statistic includes typical ANOVA test statistics. It is known that the null distribution of T converges to χ² when the sample size n is large under an adequate condition of the design matrix. We extend this result by obtaining an asymptotic expansion under general condition. Next, asymptotic expansions of one- and two-way test statistics are obtained by using this general one. Numerical accuracies are studied for some approximations of percent points and actual test sizes of T for two-way ANOVA test case based on the limiting distribution and an asymptotic expansion.     

Comparative analysis of two asymptotic approaches based on integral manifolds

A comparative analysis of the two powerful asymptotic methods,ILDM and MIM (intrinsic low-dimensional manifolds; method ofinvariant manifold), is presented in the paper. The two methodsare based on the general theory of integral manifolds. The ILDMmethod is able to handle large systems of ODEs, whereas theMIM method treats systems with a limited number of unknown variables.The MIM method allows one to conduct analytical explorationof the original system and to obtain final expressions in compactform, whereas the ILDM method is a numerical approach that yieldsthe numerical form of the desired surface. The ILDM method workswell in a region where a rough splitting of the initial systemexists. Regions of the phase space where splitting does notexist are problematic for the ILDM method. In these regionsthe MIM method provides additional information regarding thedynamical behaviour of the system. A number of simple examplesare considered and analysed. It is shown that for the Semenovmodel (singularly perturbed system of ODEs) the ILDM methodgives a surface which appears close to the first order (withrespect to the corresponding small parameter) approximationof the stable (attracting) invariant manifolds. The complementaryproperties of the two asymptotic approaches suggests a feasiblecombination of the two methods, which is the subject of a futurework.     

工薪类个税征收标准对调节居民收入分配作用的统计分析

个人所得税一直是中国老百姓最关注的话题之一,2011年个税征收标准改革的问题再次引起大家的关注,主要焦点集中在工资、薪金类的个税征收的起征点和累进税率。本文选择2001至2010年31个省份的19行业的平均工资为基础数据,运用SPSS统计分析软件分别按省份和行业作为因子对税前和税后的平均工资做方差分析,利用假设检验的P值构造统计量,定义了调节比和调节得分两个评价指标,用这两个指标衡量个人所得税征收标准对缩小工资差距的效用。本文中该模型把个税征收标准对调节居民收入分配的效果数量化,通过得分指标的变动说明过去两次个税征收标准调整的必要性以及今年审议的第四套个人所得税征收标准草案的优劣。还可以通过该模型构建的指标对某套个人所得税的征收标准是否适应当前经济发展需要起到参考作用。