A Note on Wald's Type Chi-squared Tests of Fit

The Wald's method for constructing chi-squared tests of fit has been formulated more accurately. It is shown that Wald's type statistics will follow the central chi-squared distribution if and only if the limit covariance matrix of standardized frequencies will not depend on unknown parameters. Several examples that illustrate this important fact are presented. In particular, it is shown that the goodness-of-fit statistic developed by Moore and Stubblebine does not follow the chi-squared limit distribution, and, hence, cannot be used for testing multivariate normality.     

TESTING THE AGREEMENT OF TWO QUANTITATIVE ASSAYS IN INDIVIDUAL MEANS

ABSTRACT

Existing approaches for the statistical evaluation of the agreement of two quantitative assays in terms of individual means are either based on a linear model and some stringent assumptions or comparisons of averages of individual means. Furthermore, the related statistical tests for some of these approaches are not valid in the sense that the sizes of these tests are not exactly the same as the nominal size even asymptotically. In this paper we propose a new method, which produces exact statistical tests that are easy to compute. When independent replicates are available, the proposed method requires very little or no assumption on the individual error variances. Simulation results show that the proposed tests perform better than some existing tests. Some examples are presented for illustration.     

Local GMM Estimation of Semiparametric Panel Data with Smooth Coefficient Models

In this article, we consider the estimation of semiparametric panel data smooth coefficient models. We propose a class of local generalized method of moments (LGMM) estimators that are simple and easy to implement in practice. We show that the proposed LGMM estimators are consistent and asymptotically normal. Monte Carlo simulations suggest that our proposed estimator performs quite well in finite samples. An empirical application using a large panel of U.K. firms is also presented.     

Amemiya‘s generalized least squares and tests of overidentification in simultaneous equation models with qualitative or limited dependent variables

Amemiya's generalized least squares method for the estimation of simultaneous equation modeis with qualitative or limited dependent variables is known to be efficient relative to many popular two stage estimators. This note points out that test statistics for overidentification restrictions can be obtained as by-products of Amerniya's generalized least squares procedure. Amemiya's procedure is shown to be a minimum chisquare method. The Amemiya procedure is valuable both for efficient estimation and for model evaluation of such models.     

俄罗斯、波兰固定资产投资统计制度和固定资本形成总额核算方法研究

本文从理论和实践的角度出发,深入研究了俄罗斯和波兰固定资产投资的统计原则、统计方法、统计范围和统计信息发布等内容,认真梳理了两国固定资本形成总额核算的标准、原则和方法。借鉴两国经验,对我国开展固定资产投资统计制度方法改革的原则和方法提出了意见和建议。     

基尼系数的区间估计及其应用

 本文给出了收入为离散分布的三种计算基尼系数的新方法。利用收入份额法导出了基尼系数协方差算法的离散形式,并因此产生了计算基尼系数的回归系数法。文章重点讨论了基尼系数进行区间估计的两种方法,这些方法也适用于集中度指数,因而它们在测度社会经济领域的不平等中具有着十分广泛的用途。实际应用表明,新算法有效地简化了对基尼系数区间估计的标准差估算。     

EVVMA and cusum control charts in the presence of correlation

The statistical properties of control charts are usually evaluated under the assumption that the observations from the process are independent. For many processes however, observations which are closely spaced in time will be correlated. This paper considers EWMA and CUSUM control charts for the process mean when the observations are from an AR(1) process with additional random error. This simple model may be a reasonable model for many processes encountered in practice. The ARL and steady state ARL of the EWMA and CUSUM charts are evaluated numerically using an integral equation approach and a Markov chain approach. The numerical results show that correlation can have a significant effect on the properties of these charts. Tables are given to aid in the design of these charts when the observations follow the assumed model.     

Book reviews

Donald J. Koosis: Statistics. A Self-Teaching Guide, Fourth Edition. Wiley 1997, ISBN 0-471-14688-9

Christopher C. Heyde: Quasi-Likelihood and Its Applications, Springer Series in Statistics, 1997, pp. 235, [ISBN 0-387-98225-61

Jeffrey S. Simonoff: Smoothing Methods in Statistics, Springer Series in Statistics, 1996, pp. 338

Andr´e I. Khuri, Thomas Mathew and Birmal K. Sinha: Statistical Tests for Mixed Linear Models, Wiley Series in Probability and Statistics, 1998, pp. 352, PSBN 0-471-1 5653-11

Ronald Christensen: Log-Linear Models and Logistic Regression, Springer Texts in Statistics, 1997, pp. 483, [ISBN 0-387-98247-71

E. L. Lehmann: Testing Statistical Hypotheses, Springer Texts in Statistics, 1997, pp. 600, [ISBN 0-387-94919-41

S. R. Searle, G. Casella and Ch. E. McCulloch: Variance Components, Wiley and Sons, 1992, pp. 496, [ISBN 0-471-62162-51

B. J. T. Morgan: Analysis of Quantal Response Data, Chapman & Hall, 1992, pp. 51 1

Carl D. Huberty: Applied Discriminant Analysis, Wiley and Sons, 1994, pp. 490

C. R. Rao and H. Toutenburg: Linear Models. Least Squares and Alternatives, Springer Series in Statistics, 1995, 188 pp., [ISBN 0-387-94562-81     

Robust Correlation Structure for Multivariate Failure Time Data

When incomplete repeated failure times are collected from a large number of independent individuals, interest is focused primarily on the consistent and efficient estimation of the effects of the associated covariates on the failure times. Since repeated failure times are likely to be correlated, it is important to exploit the correlation structure of the failure data in order to obtain such consistent and efficient estimates. However, it may be difficult to specify an appropriate correlation structure for a real life data set. We propose a robust correlation structure that can be used irrespective of the true correlation structure. This structure is used in constructing an estimating equation for the hazard ratio parameter, under the assumption that the number of repeated failure times for an individual is random. The consistency and efficiency of the estimates is examined through a simulation study, where we consider failure times that marginally follow an exponential distribution and a Poisson distribution is assumed for the random number of repeated failure times. We conclude by using the proposed method to analyze a bladder cancer dataset.