Quasi-random resampling for the bootstrap

Quasi-random sequences are known to give efficient numerical integration rules in many Bayesian statistical problems where the posterior distribution can be transformed into periodic functions on then-dimensional hypercube. From this idea we develop a quasi-random approach to the generation of resamples used for Monte Carlo approximations to bootstrap estimates of bias, variance and distribution functions. We demonstrate a major difference between quasi-random bootstrap resamples, which are generated by deterministic algorithms and have no true randomness, and the usual pseudo-random bootstrap resamples generated by the classical bootstrap approach. Various quasi-random approaches are considered and are shown via a simulation study to result in approximants that are competitive in terms of efficiency when compared with other bootstrap Monte Carlo procedures such as balanced and antithetic resampling.     

重庆普通高校学科建设与布局结构调整的若干思考

加强学科建设与布局结构调整既是高校内涵式发展的基本内容,也是高等教育主动适应经济社会发展的重要举措和基本途径。文章通过分析加快重庆普通高校学科建设与布局结构调整的时代背景和现实要求,提出重庆普通高校学科建设与布局结构调整应以"314"总体部署为总纲,围绕"科学发展、富民兴渝"总任务,主动适应"五大功能区"建设,按照"适应需求、创新引领,扩大规模、调整结构,内涵发展、提升水平,统筹建设、重点突破,创新机制、协同推进"的基本思路,以提升学科创新能力和水平、支撑国家和地方经济社会发展为主线,以育人为根本,以质量为核心,大力增强重庆市普通高校学科建设的优势特色和核心竞争力,为在西部率先实现全面建设小康社会目标提供有力支撑。     

刍议民办本科高校优秀师资的引进

论述民办本科高校引进优秀师资的重要性和迫切性,从人才观、制度和环境建设、教学与科研关系等多方面探讨如何引进优秀师资问题,提出了若干有益的对策建议。     

普通初中以奖学奖教构建和谐向上的人文学风和校风

初中短短的三年却是人生的一个较为重要的转折期和塑造期,这个阶段的学生很容易受到来自老师和同学们或褒或贬,促善或流俗的成长影响。所以要让普通初中每一个学生顺利而烂漫地度过他们的花季,必须构建一个和谐向上的人文化的学风和校风。根据初中生的身心特点和教育规律,汲取传统教育和地方文化的优势,我们拟以一所普通初中作为范例,进行奖学奖教人文学风和校风建设探索。     

高等师范院校推行顶岗实习的实践意义

近年来,高校师范生顶岗实习作为改革教师教育的一项战略性重要举措备受关注。顶岗实习既是高校师范教育的需要,也是培养师范生四种能力的有效途径,同时也使贫困地区的基础教育获得持续的、较高水准的师资补充。顶岗实习是一项"顶岗学生、师范院校、实习学校"三方共赢的系统工程,具有十分重要的现实意义。     

高校校规及其合法性管窥

高校校规是高校进行内部管理的依据和准则,也是各个高校提高管理水平和效率的有效手段,合法是法治对之所提的基本要求,也是构建和谐校园的重要因素之一。然而,近几年来,学校被诉和学校败诉的大量事实证明:高校校规中存在着许多与大学生合法权利保护相违背的条款。因此,合法又合理的校规,其意义不仅在于可以提高高校的工作效率,更重要的是可以推动高校的良性发展,构建和谐校园。     

Truncated regular vines in high dimensions with application to financial data

Using only bivariate copulas as building blocks, regular vine copulas constitute a flexible class of high‐dimensional dependency models. However, the flexibility comes along with an exponentially increasing complexity in larger dimensions. In order to counteract this problem, we propose using statistical model selection techniques to either truncate or simplify a regular vine copula. As a special case, we consider the simplification of a canonical vine copula using a multivariate copula as previously treated by Heinen & Valdesogo ( 2009 ) and Valdesogo ( 2009 ). We validate the proposed approaches by extensive simulation studies and use them to investigate a 19‐dimensional financial data set of Norwegian and international market variables. The Canadian Journal of Statistics 40: 68–85; 2012 © 2012 Statistical Society of Canada     

Conditional Extremes in Asymmetric Financial Markets

ABSTRACT

The global financial crisis of 2007–2009 revealed the great extent to which systemic risk can jeopardize the stability of the entire financial system. An effective methodology to quantify systemic risk is at the heart of the process of identifying the so-called systemically important financial institutions for regulatory purposes as well as to investigate key drivers of systemic contagion. The article proposes a method for dynamic forecasting of CoVaR, a popular measure of systemic risk. As a first step, we develop a semi-parametric framework using asymptotic results in the spirit of extreme value theory (EVT) to model the conditional probability distribution of a bivariate random vector given that one of the components takes on a large value, taking into account important features of financial data such as asymmetry and heavy tails. In the second step, we embed the proposed EVT method into a dynamic framework via a bivariate GARCH process. An empirical analysis is conducted to demonstrate and compare the performance of the proposed methodology relative to a very flexible fully parametric alternative.     

Robustness and monotonicity properties of generalized correlation coefficients

A new class of generalized correlation coefficients that contains the Pearson and Kendall statistics as special cases was defined by Chinchilli et al. (2005) and applied to the estimation of correlations coefficients within the context of 2×2 cross-over designs for clinical trials. In this paper, we determine the infinitesimal robustness and local stability properties of these generalized correlation coefficients by deriving their corresponding influence functions. For cases in which the population distribution is a bivariate normal or a mixture of bivariate normal distributions we obtain explicit formulas, and establish monotonicity and sign-reverse rule properties of the generalized correlation coefficients.     

State space modeling of multiple time series: a comment

This paper provides guidance in choosing k₁ andk₂ of the double k-class (KK) estimator such that it will improve upon both the ordinary least squares (OLS) and Stein-rule (SR) estimators in predictive mean squared error (PMSE). Asymptotic bias and mean squared error (MSE) results are derived for nonnormal and other cases. A simulation compares the KK estimator with the OLS and SR estimators.