R–estimation of normed bivariate density functions

Normed bivariate density funtions were introduced by HOEFFDING (1940/41). In the present paper estimators for normed bivariate ranks and on a FOURIER series expansion in LEGENDRE polynomials. The estimation of normed bivarate density functions under positive dependence is also described     

BARTLETT CORRECTED LIKELIHOOD RATIO TESTS IN LOCATION-SCALE NONLINEAR MODELS

The paper derives Bartlett corrections for improving the chisquare approximation to the likelihood ratio statistics in a class of location-scale family of distributions, which encompasses the elliptical family of distributions and also asymmetric distributions such as the extreme value distributions. We present, in matrix notation, a Bartlett corrected likelihood ratio statistic for testing that a subset of the nonlinear regression coefficients in this class of models equals a given vector of constants. The formulae derived are simple enough to be used analytically to obtain several Bartlett corrections in a variety of important models. We show that these formulae generalize a number of previously published results. We also present simulation results comparing the sizes and powers of the usual likelihood ratio tests and their Bartlett corrected versions when the scale parameter is considered known and when this parameter is uncorrectly specified.     

The Relationship of Expectancies to the Transtheoretical Model of Change in College Smokers

Abstract

Efforts on the part of the sci en tific com mu nity have resulted in in creased knowl edge about to bacco ad die tion and im proved treat ment ef fi cacy. De spite these gains, how ever, our un der stand ing of to bacco ad die tion re mains in com plete. Two el e ments that may help il lu-mi nate the knowl edge of this ad die tion pro cess and pro vide im pli ca tions for treat ment are the Transtheoretical Model of Change and the con cept of ex pec tan cies. This project is a be gin ning step in ex plor ing the re la tion ship be tween the transtheoretical model and fac ets of ex pec tan cies among col lege smokers.     

跨文化交际教育中的交流模式解析

伴随着全球化进程，跨文化交际过程中对于交流技巧的关注愈来愈多。交流的方式及过程直接影响到交流效果的好坏，于是如何使用得当的方式处理交流过程中涉及的信息、意义便成为保障顺利交流的关键。文本试从解析交流过程中信息的产生及走向为出发点，重点探讨改进意义的方式，并最终建构跨文化交际教育中更为科学合理的交流模式。     

基于测井资料的低孔低渗储层产能预测研究

针对低孔低渗储层产能预测模型受敏感因素影响大，主次因素在低产情况下区别不明显，产能预测评价相对较困难等实际问题，以准噶尔盆地夏子街地区夏77井、夏79井为例，开展低孔低渗储层产能预测的前期试验研究，对多个产能预测模型及其适用条件进行了对比分析，从Darcy模型、Jones（1976）模型、Vogel/Harrison（1968）模型、裂缝模型中进行优选和调试。通过分析产能预测模型结果与测试结果在产量上的相关性，表明基于测井资料的预测结果与试油测试结果相当吻合，从而确认产能预测模型结果的可靠性。     

丙烯精馏塔的建模及其先进控制方法研究

精馏过程是化工、石油、医药等领域常见的生产过程，由于其非线性、时变性和强耦合等特点，使建模、控制与优化成为理论与实践研究中的难点。本文以一个二元丙烯精馏塔为研究对象，在由物料及能量平衡原理推导出精馏过程数学模型的基础之上，采用基于集结法的动力学模型降阶处理方法对原模型进行降阶，最后为该精馏塔模型设计了基于PID神经网络的解耦控制器。     

A Bayesian Evidence Synthesis for Estimating Campylobacteriosis Prevalence

Stakeholders making decisions in public health and world trade need improved estimations of the burden‐of‐illness of foodborne infectious diseases. In this article, we propose a Bayesian meta‐analysis or more precisely a Bayesian evidence synthesis to assess the burden‐of‐illness of campylobacteriosis in France. Using this case study, we investigate campylobacteriosis prevalence, as well as the probabilities of different events that guide the disease pathway, by (i) employing a Bayesian approach on French and foreign human studies (from active surveillance systems, laboratory surveys, physician surveys, epidemiological surveys, and so on) through the chain of events that occur during an episode of illness and (ii) including expert knowledge about this chain of events. We split the target population using an exhaustive and exclusive partition based on health status and the level of disease investigation. We assume an approximate multinomial model over this population partition. Thereby, each observed data set related to the partition brings information on the parameters of the multinomial model, improving burden‐of‐illness parameter estimates that can be deduced from the parameters of the basic multinomial model. This multinomial model serves as a core model to perform a Bayesian evidence synthesis. Expert knowledge is introduced by way of pseudo‐data. The result is a global estimation of the burden‐of‐illness parameters with their accompanying uncertainty.     

On the simple step-stress model for two-parameter exponential distribution

In this paper, we consider the simple step-stress model for a two-parameter exponential distribution, when both the parameters are unknown and the data are Type-II censored. It is assumed that under two different stress levels, the scale parameter only changes but the location parameter remains unchanged. It is observed that the maximum likelihood estimators do not always exist. We obtain the maximum likelihood estimates of the unknown parameters whenever they exist. We provide the exact conditional distributions of the maximum likelihood estimators of the scale parameters. Since the construction of the exact confidence intervals is very difficult from the conditional distributions, we propose to use the observed Fisher Information matrix for this purpose. We have suggested to use the bootstrap method for constructing confidence intervals. Bayes estimates and associated credible intervals are obtained using the importance sampling technique. Extensive simulations are performed to compare the performances of the different confidence and credible intervals in terms of their coverage percentages and average lengths. The performances of the bootstrap confidence intervals are quite satisfactory even for small sample sizes.     

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.     

A Conditional Approach for Regression Analysis of Longitudinal Data with Informative Observation Time and Non-negligible Observation Duration

Recently, there has been a great interest in the analysis of longitudinal data in which the observation process is related to the longitudinal process. In literature, the observation process was commonly regarded as a recurrent event process. Sometimes some observation duration may occur and this process is referred to as a recurrent episode process. The medical cost related to hospitalization is an example. We propose a conditional modeling approach that takes into account both informative observation process and observation duration. We conducted simulation studies to assess the performance of the method and applied it to a dataset of medical costs.