A weighted symmetric cointegration test

Weighted symmetric estimation is employed to develop a new test for cointegration. Using Monte Carlo simulation, the resulting test is shown to possess greater power than alternative existing tests.     

Corrected maximum likelihood estimators in heteroscedastic symmetric nonlinear models

In this article, we derive general matrix formulae for second-order biases of maximum likelihood estimators (MLEs) in a class of heteroscedastic symmetric nonlinear regression models, thus generalizing some results in the literature. This class of regression models includes all symmetric continuous distributions, and has a wide range of practical applications in various fields such as engineering, biology, medicine and economics, among others. The variety of distributions with different kurtosis coefficients than the normal may give more flexibility in the choice of an appropriate distribution, particularly to accommodate outlying and influential observations. We derive a joint iterative process for estimating the mean and dispersion parameters. We also present simulation studies for the biases of the MLEs.     

Error reduction in density estimation under shape restrictions

For the problems of nonparametric estimation of nonincreasing and symmetric unimodal density functions with bounded supports we determine the projections of estimates onto the convex families of possible parent densities with respect to the weighted integrated squared error. We also describe the method of approximating the analogous projections onto the respective density classes satisfying some general moment conditions. The method of projections reduces the estimation errors for all possible values of observations of a given finite sample size in a uniformly optimal way and provides estimates sharing the properties of the parent densities.     

Comparison of estimators of the location parameter using pitman's closeness criterion

Necessary and sufficient conditions for a linear estimator to dominate another linear estimator of a location parameter under the Pitman's criterion of comparison are discussed. Consequently it is demonstrated that a linear biased estimator can not dominate a linear unbiased estimator under Pitman's criterion and that the sample mean is the Closest Linear Unbiased Estimator (CLUE). It is also shown that the ridge regression estimator with a known biasing constant can not dominate the ordinary least squares estimator. If an estimator δdominates an estimator δin the average loss sense then sufficient conditions are obtained under which δis also preferred over δunder Pitman's criterion. Further we obtain sufficient conditions under which preference under the Pitman's criterion will lead to preference under the mean squared error sense.     

Log-linear model analysis of the semi-symmetric intraclass contingency table

This paper addresses the problem of analyzing a three-way contingency table that is upper-triangular, and a priori symmetric within layers. The log-linear model is modified to handle this kind of table, and maximum likelihood estimation is carried out for the modified log-linear model. This leads to an expression of the maximum likelihood estimates exclusively in terms of the observed cell counts. It is skin this analysis is equivalent to an application of the gone log-linear model to an artificially complete table, obtain. by splitting the off-diagonal cells in half within layers. This analysis is used in analyzing the results of a study done to determine the effect of the sex-linked dwarfing gene in male chickens on resistance to E. coli infection; the conclusion differs from that of a previous analysis of the same data (see Norwood and Hinkelmann 1978). It is found, in fact, that the structure of association among the two allele variables and the disease variable is somewhat more complex than previously proposed. A second example is taken from Ishii (1960). Finally, collapsibility conditions for the modified log-linear model, as well as various other sampling plans and limitations to the testing procedure, are discussed.     

应用范成法加工对称凸轮轮廓的研究

对称凸轮轮廓的加工方法有多种,但各有不足,为了克服原有的加工方法的缺陷,提出了范成法加工对称凸轮轮廓曲线的方法,并阐明了范成法加工对称凸轮轮廓曲线的原理及实现方法.利用范成法加工对称凸轮,不但解决了其他加工方法加工接拍长、加工成本高甚至无法加工的问题,而且加工精度高,操作简单可靠,可广泛用于各种批量对称凸轮的加工生产.     

语篇象似性与翻译

象似性存在于语言的各个层面上。在篇章中的象似性现象有重要的表意功能。因此,翻译不仅仅是语言符号之间的转换,同时也要受篇章象似性的制约。文章主要从距离象似性,语音象似性,形状象似性和对称象似性来讨论篇章象似性对翻译的制约。     

Stochastic analysis of covariance when the error distribution is long-tailed symmetric

In this study, we consider stochastic one-way analysis of covariance model when the distribution of the error terms is long-tailed symmetric. Estimators of the unknown model parameters are obtained by using the maximum likelihood (ML) methodology. Iteratively reweighting algorithm is used to compute the ML estimates of the parameters. We also propose new test statistic based on ML estimators for testing the linear contrasts of the treatment effects. In the simulation study, we compare the efficiencies of the traditional least-squares (LS) estimators of the model parameters with the corresponding ML estimators. We also compare the power of the test statistics based on LS and ML estimators, respectively. A real-life example is given at the end of the study.     

变差可积鞅及条件变差可积鞅的最优系数不等式

设f是条件变差可积鞅 ,则有‖f‖p≤ 1P‖f‖ap　 0 相似文献