Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

双波长比值法测定水杨酸、间苯二酚、对氨基苯甲酸的含量

依据水杨酸、间苯二酚、对氨基苯甲酸三组分的比值光谱特征,以对氨基苯甲酸为干扰组分,选择241nm、278nm作为测定水杨酸的波长;以水杨酸作为干扰组分,选择214nm、240nm作为测定间苯二酚的波长;以间苯二酚作为干扰组分,选择222nm、279nm作为测定对氨基苯甲酸的波长.结果显示,水杨酸浓度在1~80mg/L,基本二酚浓度在0.8~40mg/L,对氨基苯甲酸浓度在0.4~40mg/L范围内具有良好的线性关系.本方法具有测定波长少,光谱分离能力强、计算简单、能在低档分光光度计上实现、易于推广等特点.     

Visualization of generalized mean estimators using auxiliary information in survey sampling

Abstract

The mean estimators with ratio depend on multiple auxiliary variables and unknown parameters in a finite population setting. We propose a new generalized approach with matrices for modeling the mutivariate mean estimators with two auxiliary variables. Our approach brings naturally a graphical analysis for comparing mean estimators.     

湖北省乡镇企业1978—2002年发展概况、问题及对策研究

1978～2002年,湖北省乡镇企业在企业单位数量、对经济增长贡献及转移农村剩余劳动力等方面对该省经济产生了重要的推动作用。然而,随着市场经济体制的深入发展和不断完善,乡镇企业发展也遇到了前所未有的困难。本文在深入分析当前乡镇企业所面临的问题基础上,提出了乡镇企业未来发展的战略对策。     

上证30指数股市盈率实证分析

通过对2000年上证30指数股市盈率水平及其影响因素进行实证分析,可以发现,其中股息支付率、每股收益增长率、行业平均市盈率对股票P/E值起主要的解释作用,而股本规模因素,解释力却有限,除每股收益增长率外,各变量的相关性与理论分析基本一致.     

农业高科技企业成长机会价值量化模型构建及其应用

农业高科技企业成长机会包括农业高新技术研发和市场推广,是一个系列递进买方期权。其价值是农业高科技企业价值的核心部分。本文利用二项式分布模型构建了时间和概率因素下成长机会的期权形式价值量化模型,总结了农业高科技企业的期权性质及其特点,并以此为基础,进一步讨论了成长机会价值量化模型在农业高科技企业价值评估中的应用。     

五点“希望”是大学生成长的方向

理想远大和热爱祖国、追求真理和勇于创新、德才兼备和全面发展、视野开阔和胸怀宽广、知行统一和脚踏实地是 2 1世纪大学生成长的方向。     

指数级数的增长性和值分布

本文研究了随机狄里克莱级数 在随机变量序列{Xn}独立（可不同分布）以及满足等条件时的增长性以及值分布,得到了一些新的结果.     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.