Human Reliability Analysis by Fuzzy "CREAM"

This article proposes a systematic procedure for computing probabilities of operator action failure in the cognitive reliability and error analysis method (CREAM). The starting point for the quantification is a previously introduced fuzzy version of the CREAM paradigm that is here further extended to account for: (1) the ambiguity in the qualification of the conditions under which the action is performed (common performance conditions, CPCs) and (2) the fact that the effects of such conditions on human performance reliability may not all be equal.     

SOME SECOND ORDER ASYMPTOTICS IN EXPONENTIAL FAMILY NON-LINEAR REGRESSION MODELS (A GEOMETRIC APPROACH)

The differential geometric framework of Amari (1982a, 1985) is applied to the study of some second order asymptotics related to the curvatures for exponential family nonlinear regression models, in which the observations are independent but not necessarily identically distributed. This paper presents a set of reasonable regularity conditions which are needed to study asymptotics from a geometric point of view in regression models. A new stochastic expansion of a first order efficient estimator is derived and used to study several asymptotic problems related to Fisher information in terms of curvatures. The bias and the covariance of the first order efficient estimator are also calculated according to the expansion.     

服务台需要检修的M／PH／1排队模型分析

本文研究了一个M／PH／1排队,这个排队系统的服务台每服务完一定量的顾客，就要进行一闪检修，然后才继续服务。在检修时间服从位相（PH）分布时，本文求出了这个系统达到平衡的条件以及有关排队率和可靠性的指标。顺便求出了普通的M／PH／1系统第M个顾客离去时刻的分布。     

研究生招生工作中的小概率事件及其预防

利用小概率原理分析研究生招生工作中的突发事件,提出了导致小概率事件发生的原因有重复效应、数量累积效应和群众检验效应,认为在招生工作中要树立小概率事件意识,科学设计招生工作流程,建立应对小概率事件的制度,以更有效地应对小概率事件。     

我国当前教育诚信缺失的原因与对策分析

从陕西洋县高考替考事件谈起,列举了目前教育诚信缺失在学生、教师、教育部门和学校的不同表现,分析了诚信缺失的可能原因,并提出了营造诚信大环境、提高教师诚信素养、加强学生道德教育、建立教师和学生诚信信用体系等对策。     

论六朝启文的骈化及其艺术得失

在六朝的诸种文体之中，启文的骈化较晚，到刘宋时期才出现骈体之作。这一时期，启文也开始产生新变，出现了谢物小启。尤其到了梁代，谢物小启呈雨后春笋之势，不论是在数量上，还是在艺术成就上，都远远超过了用兼表奏的启文，并成为六朝后期四六化色彩很强的一种文体。     

Bayesian inference and model comparison for asymmetric smooth transition heteroskedastic models

Inference, quantile forecasting and model comparison for an asymmetric double smooth transition heteroskedastic model is investigated. A Bayesian framework in employed and an adaptive Markov chain Monte Carlo scheme is designed. A mixture prior is proposed that alleviates the usual identifiability problem as the speed of transition parameter tends to zero, and an informative prior for this parameter is suggested, that allows for reliable inference and a proper posterior, despite the non-integrability of the likelihood function. A formal Bayesian posterior model comparison procedure is employed to compare the proposed model with its two limiting cases: the double threshold GARCH and symmetric ARX GARCH models. The proposed methods are illustrated using both simulated and international stock market return series. Some illustrations of the advantages of an adaptive sampling scheme for these models are also provided. Finally, Bayesian forecasting methods are employed in a Value-at-Risk study of the international return series. The results generally favour the proposed smooth transition model and highlight explosive and smooth nonlinear behaviour in financial markets.     

Properties of Bayes Factors Based on Test Statistics

Abstract.  This article examines the consistency, interpretation and application of Bayes factors constructed from standard test statistics. Primary conclusions are that Bayes factors based on multinomial and normal test statistics are consistent for suitable choices of the hyperparameters used to specify alternative hypotheses, and that such constructions can be extended to obtain consistent Bayes factors based on likelihood ratio statistics. A connection between Bayes factors based on likelihood ratio statistics and the Bayesian information criterion is exposed, as is a connection between Bayes factors based on F statistics and parametric Bayes factors based on normal-inverse gamma models. Similarly, Bayes factors based on chi-squared statistics for multinomial data are shown to provide accurate approximations to Bayes factors based on multinomial/Dirichlet models. An illustration of how the simple form of these Bayes factors can be exploited to generate easily interpretable summaries of the experimental 'weight of evidence' is provided.     

少数民族传统文化中现代价值的认识和继承——以神话传说中的生态思想为例

研究和发掘少数民族传统文化中的现代价值,不仅有利于唤起人们对保护民族地区文化生态重要性的认识,而且也是更好地继承和发展少数民族传统文化的需要。文章以少数民族神话传说中蕴含的生态思想为例,指出在少数民族传统文化流失和变异不断加剧的背景下,对其现代价值的研究,既要重视文献资料的发掘,也不能忽视田野调查的结论,只有将两者结合起来,才能得出更为切合实际的结论。     

Exact inference for a simple step-stress model with competing risks for failure from exponential distribution under Type-II censoring

In reliability analysis, accelerated life-testing allows for gradual increment of stress levels on test units during an experiment. In a special class of accelerated life tests known as step-stress tests, the stress levels increase discretely at pre-fixed time points, and this allows the experimenter to obtain information on the parameters of the lifetime distributions more quickly than under normal operating conditions. Moreover, when a test unit fails, there are often more than one fatal cause for the failure, such as mechanical or electrical. In this article, we consider the simple step-stress model under Type-II censoring when the lifetime distributions of the different risk factors are independently exponentially distributed. Under this setup, we derive the maximum likelihood estimators (MLEs) of the unknown mean parameters of the different causes under the assumption of a cumulative exposure model. The exact distributions of the MLEs of the parameters are then derived through the use of conditional moment generating functions. Using these exact distributions as well as the asymptotic distributions and the parametric bootstrap method, we discuss the construction of confidence intervals for the parameters and assess their performance through Monte Carlo simulations. Finally, we illustrate the methods of inference discussed here with an example.