Estimation of noncentrality parameters

We propose some estimators of noncentrality parameters which improve upon usual unbiased estimators under quadratic loss. The distributions we consider are the noncentral chi-square and the noncentral F. However, we give more general results for the family of elliptically contoured distributions and propose a robust dominating estimator.     

论文艺复兴时期人文主义与科学精神的塑造

文艺复兴时期的人文主义重视世俗生活和人的现实享乐,把对财富的拥有看作享受的根本基础,驱动了新航路的开辟,为近代科学精神的塑造奠定了实践基础。人文主义唤起了人们探求人自身和客观世界的奥秘,用理性的眼光观察世俗的社会生活,用求证试验的方法验证真理。人文主义否认权威;追求知识,捍卫真理,从而塑造了科学精神。     

20世纪三四十年代西北地区宗教生活的变迁

20世纪三四十年代,随着民族危机的加深和国民政府开发西北战略的实施,西北地区民众的宗教生活也发生了某些变化,具体表现为佛教信仰衰而复振,基督教信仰趋于兴盛,伊斯兰教活动与时俱进,道教信仰的衰落与留存;民间诸神信仰并行不悖。这从一个侧面反映了当时西北地区民众的精神状态和社会生活方式的变迁。     

进化的精神和生活的道德——鲁迅与契诃夫人生哲学比较论

面对着现实困境的鲁迅与契诃夫都珍视人生的价值,强调人的自我意识与主体力量,但是由于文化传统与历史背景的不同,他们的人生哲学各具特色。鲁迅的人生哲学体现了战斗的进化精神,契诃夫的人生哲学探讨了超脱的生活道德。     

从生命美学探讨生命教育

青少年的生命充满着生机与活力,展现出未来的希望与辉煌。而现实的教育主要局限于让认知和理性取代了生命的存在,往往忽视关注青少年的心灵世界。从生命美学探讨生命教育,实现生命本真的教育。     

贾岛为僧及还俗时间地点考

贾岛出家及还俗的时间地点问题是贾岛生平仕历研究的一个重要问题。通过对现有史料记载以及贾岛等人诗文的考证分析,可知贾岛贞元九年(793)在北岳恒山出家为僧,时年15岁。后曾住洛阳石楼及嵩山一带。贞元十七年(801)在石楼与韩愈初次相识。元和六年(811)春在洛阳又遇到时任河南县令的韩愈,同年秋跟随韩愈赴长安准备应进士举,但并未马上还俗。冬十一月返回家乡范阳,处理僧俗事务。至迟于次年即元和七年(812)春还俗并参加进士考试,时年34岁。     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

新时期的马克思主义伦理学研究如何"回到马克思"?

在以往的马克思主义伦理学研究中,不同程度地存在对马克思和恩格斯的种种偏离。新时期的马克思主义伦理学研究要进一步向前发展,就必须把“回到马克思”和“回到现实生活”结合起来,根据社会主义初级阶段的实际,确立马克思主义伦理学研究的出发点和立足点。     

2005年冯友兰哲学思想研究综述

冯友兰先生的哲学思想在中国近代哲学思想中占有非常重要的地位,他的“三史”和“六书”影响广泛,他的“新理学”体系,是对宋明理学的继承和发展,他的人生境界说,还有融入其中的中西文化观,对中国哲学发展的思考无不表明冯友兰先生是一位伟大的哲学家和思想家。将2005年学术界关于冯友兰哲学思想研究的论文作一综述,以纪念冯友兰先生诞辰110周年。     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.