A NEW APPROACH TO MAXIMUM LIKELIHOOD ESTIMATION OF THE THREE-PARAMETER GAMMA AND WEIBULL DISTRIBUTIONS

A new approach, is proposed for maximum likelihood (ML) estimation in continuous univariate distributions. The procedure is used primarily to complement the ML method which can fail in situations such as the gamma and Weibull distributions when the shape parameter is, at most, unity. The new approach provides consistent and efficient estimates for all possible values of the shape parameter. Its performance is examined via simulations. Two other, improved, general methods of ML are reported for comparative purposes. The methods are used to estimate the gamma and Weibull distributions using air pollution data from Melbourne. The new ML method is accurate when the shape parameter is less than unity and is also superior to the maximum product of spacings estimation method for the Weibull distribution.     

AN EXCLUSIVE REGRESSORS BINARY MIXTURE MODEL WITH AN APPLICATION TO LABOUR SUPPLY

This paper suggests a new type of mixture regression model, in which each mixture component is explained by its own regressors. Thus, the dependent variable can be driven by one of several unobservable explanatory mechanisms, each of which has its own distinct variables. An extension of the simulated annealing algorithm is introduced to fit this general mixture model. The paper also suggests a new technique for estimating the covariance matrix of estimators in a mixture model. Finally, empirical studies of a labour supply example show that our proposed model can perform much better than conventional logistic or mixture models.     

COMBINING INFORMATION FROM LINEAR MODELS ON POSSIBLY DIFFERENT SCALES

This paper examines the joint statistical analysis of M independent data sets, the jth of which satisfies the model λ_j Y_j=X_jB +ε_j, where the λ_j are unknown and the ε_i are normally distributed with a known correlation structure. The maximum likelihood equations, their asymptotic covariance matrix, and the likelihood ratio test of the hypothesis that the λ_js are all equal are derived. These results are applied to two examples.     

用XRF基本参数法定量计算多层薄膜的厚度

针对多层薄膜材料，用ＸＲＦ基本参数（ＦＰ）法定量分析计算多层薄膜试样的厚度。除了考虑直接受人射束激发产生初级荧光外，还考虑试样中其它元素初级荧光辐射而引起的层间和层内二次荧光。以计算三层膜荧光强度为例，提出各种不同情况下计算初级和次级荧光强度的表达式。讨论二次荧光相对于，总强度的贡献。计算方法也能很好地用在大于三层膜及块样的Ｘ荧光强度计算。     

多维定位误差的CAEC建模与实验研究

为对三维机的多维定位误差提供CAEC信息,本文作者提出了“点阵综合计算法”,对多维定位误差的CAEC建模、实验进行了理论与实验方法的研究。     

多因素数据重心预测方法及应用研究

本文基于数据重心概念,通过大量的研究和推导,提出数据重心参数估计理论,并利用数据重心法估计多项式回归预测模型的参数,应用于我国钢材消费量的预测。从应用的结果看,增加了我国目前钢材预测的方法。本方法能最大限度地平滑预测模型的误差,而且应用条件比最小二乘法宽松;也不会因为个别残差较大的异常点而对预测结果产生不稳定性,从而提高了拟合和预测的稳健度,计算更简捷。     

基于遗传算法的集成产销系统参数优化

为了解决供应链中生产和分销的目标不同导致的产销系统的矛盾,本文将基于需求拉动的供应链中分销节点、成品库、加工中心、原料库集成,形成一个集成的产销系统。另外通过设计合适的染色体结构和遗传算子,确定了各个子系统的最优参数,这些参数使得集成系统在满足外生需求最低服务水平的前提下整体成本达到极小化。为了保证最优参数的可行性,提出了有效染色体生成算法。对算例的分析表明,服务水平的增加并不是以总成本的增加为代价的,集成产销系统可以在提高服务水平的同时降低总成本。     

用结构参数F预测饱和烷烃水的溶解度和辛醇/水分配系数

用结构参数F预测了46种饱和烷烃水的溶解度和辛醇／水分配系数,预测结果与文献值十分接近．     

Log Gaussian Cox Processes

Planar Cox processes directed by a log Gaussian intensity process are investigated in the univariate and multivariate cases. The appealing properties of such models are demonstrated theoretically as well as through data examples and simulations. In particular, the first, second and third-order properties are studied and utilized in the statistical analysis of clustered point patterns. Also empirical Bayesian inference for the underlying intensity surface is considered.     

Asymptotic Expansions of Estimators for the Tail Index with Applications

We present asymptotic expansions for two well-known estimators of the tail index of a distribution—the Hill's estimator and the simplified Pickands' estimator. We then use the expansions to get more accurate interval estimates. Comparisons between the two estimators are also discussed.