On some mixture models based on the Birnbaum-Saunders distribution and associated inference

In this paper, we consider three different mixture models based on the Birnbaum-Saunders (BS) distribution, viz., (1) mixture of two different BS distributions, (2) mixture of a BS distribution and a length-biased version of another BS distribution, and (3) mixture of a BS distribution and its length-biased version. For all these models, we study their characteristics including the shape of their density and hazard rate functions. For the maximum likelihood estimation of the model parameters, we use the EM algorithm. For the purpose of illustration, we analyze two data sets related to enzyme and depressive condition problems. In the case of the enzyme data, it is shown that Model 1 provides the best fit, while for the depressive condition data, it is shown all three models fit well with Model 3 providing the best fit.     

Approximate bounded influence estimation for longitudinal data with outliers and measurement errors

Mixed effects models or random effects models are popular for the analysis of longitudinal data. In practice, longitudinal data are often complex since there may be outliers in both the response and the covariates and there may be measurement errors. The likelihood method is a common approach for these problems but it can be computationally very intensive and sometimes may even be computationally infeasible. In this article, we consider approximate robust methods for nonlinear mixed effects models to simultaneously address outliers and measurement errors. The approximate methods are computationally very efficient. We show the consistency and asymptotic normality of the approximate estimates. The methods can also be extended to missing data problems. An example is used to illustrate the methods and a simulation is conducted to evaluate the methods.     

A Bayesian analysis for the Block and Basu bivariate exponential distribution in the presence of covariates and censored data

In this paper, we introduce a Bayesian Analysis for the Block and Basu bivariate exponential distribution using Markov Chain Monte Carlo (MCMC) methods and considering lifetimes in presence of covariates and censored data. Posterior summaries of interest are obtained using the popular WinBUGS software. Numerical illustrations are introduced considering a medical data set related to the recurrence times of infection for kidney patients and a medical data set related to bone marrow transplantation for leukemia.     

Evolution of capital structure in east Asia—corporate inertia or endeavours?

Summary.  The paper examines the capital structure adjustment dynamics of listed non-financial corporations in seven east Asian countries before, during and after the crisis of 1997–1998. Our methodology allows for speeds of adjustment to vary, not only among firms, but also over time, distinguishing between cases of sudden and smooth adjustment. Whereas, compared with firms in the least affected countries, average leverages were much higher, generalized method-of-moments analysis of the Worldscope panel data suggests that average speeds of adjustment were lower in the worst affected countries. This holds also for the severely financially distressed firms in some worst affected countries, though the trend reversed in the post-crisis period. These findings have important implications for the regulatory environment as well as access to market finance.     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.     

Bayesian model selection for join point regression with application to age-adjusted cancer rates

Summary.  The method of Bayesian model selection for join point regression models is developed. Given a set of K +1 join point models M ₀,  M ₁, …,  M _K with 0, 1, …,  K join points respec-tively, the posterior distributions of the parameters and competing models M _k are computed by Markov chain Monte Carlo simulations. The Bayes information criterion BIC is used to select the model M _k with the smallest value of BIC as the best model. Another approach based on the Bayes factor selects the model M _k with the largest posterior probability as the best model when the prior distribution of M _k is discrete uniform. Both methods are applied to analyse the observed US cancer incidence rates for some selected cancer sites. The graphs of the join point models fitted to the data are produced by using the methods proposed and compared with the method of Kim and co-workers that is based on a series of permutation tests. The analyses show that the Bayes factor is sensitive to the prior specification of the variance σ ², and that the model which is selected by BIC fits the data as well as the model that is selected by the permutation test and has the advantage of producing the posterior distribution for the join points. The Bayesian join point model and model selection method that are presented here will be integrated in the National Cancer Institute's join point software ( http://www.srab.cancer.gov/joinpoint/ ) and will be available to the public.     

明清时期《水浒传》研究方法及其现代承传

明清时期《水浒传》研究格局主要由传统的文献学手段、晚明以降的评点式研究、思想评论的二元对立思维模式等方法所支撑。20世纪初以来,现代意义上"水浒学"的形成与丰富,虽然很大程度上归功于对种种西方理论方法的引进与采用,但传统研究方法的优势并没有被完全取代:在《水浒传》的成书、本事、版本及作者等方面,传统的文献学手段依然是最主流、最有效的途径;序跋式批评则在现代《水浒》传播中蜕变为"出版说明"、"前言"、"编者的话"等形式,仍旧发挥着"批评"的功能。20世纪初以来的《水浒传》研究多次被卷入政治斗争,其实也与明清时期《水浒传》思想评论中的二元对立思维模式有着内在的逻辑关联。     

儒家德育方法与当代大学生德育工作

儒家德育的基本方法有：权威教化法、榜样仿效法、差异培养法、熏陶管理法、自我修身法、躬行实践法等,它是儒家德育思想的重要组成部分,这些方法相互联结,相互补充,构成一个有机统一体。借鉴儒家德育方法,结合我国大学生德育实践和社会时代特征,当前高校德育工作应做到改善思想灌输法,重视典型教育法,实施分层教育法,强化感染教育法,突出自我教育法,注重实践教育法,从而不断提高当代大学生德育工作的针对性和实效性。     

以科学发展观为指导对大学生加强科学思维方法教育

科学发展观不仅是我国治国思想和发展理念,而且是当代科学思维方法的智慧结晶和理性升华。大学教育要以科学发展观为指导,探索在高等教育中对大学生进行科学发展观教育的针对性和结合点,改革大学教学方法,对大学生加强科学思维方法的教育引导。     

信息技术课程多元智力教学模式探究

多元智力理论超越了传统以语言——数理逻辑能力为中心的智力观念,它的发展对传统学科教育产生了深刻的影响,本文就信息技术课程学科特点,从多元智力角度对教学方法改革进行探讨和研究。