A matching prior based on the modified profile likelihood in a generalized Weibull stress‐strength model

Bayesian inference of a generalized Weibull stress‐strength model (SSM) with more than one strength component is considered. For this problem, properly assigning priors for the reliabilities is challenging due to the presence of nuisance parameters. Matching priors, which are priors matching the posterior probabilities of certain regions with their frequentist coverage probabilities, are commonly used but difficult to derive in this problem. Instead, we apply an alternative method and derive a matching prior based on a modification of the profile likelihood. Simulation studies show that this proposed prior performs well in terms of frequentist coverage and estimation even when the sample sizes are minimal. The prior is applied to two real datasets. The Canadian Journal of Statistics 41: 83–97; 2013 © 2012 Statistical Society of Canada     

Some Results on Comparing the Quantiles of Dependent Groups

Recently, Lombard derived an extension of the Doksum–Sievers shift function to dependent groups. This article suggests using a particular numerical method for determining the critical value, reports on the ability of the method to control the probability of a Type I error when sample sizes are small, and it provides comparisons with methods aimed at comparing deciles. It is found that for continuous distributions, Lombard's method performs well and in particular has high power relative to the other two methods considered. But when tied values can occur, now it can have relatively poor power; a method based on the Harrell-Davis estimator is found to give more satisfactory results.     

Projection Pursuit Through Relative Entropy Minimization

Projection Pursuit methodology permits to solve the difficult problem of finding an estimate of a density defined on a set of very large dimension. In his seminal article, “Projection Pursuit”, Huber (1985 Huber , P. ( 1985 ). Projection pursuit . The Annals of Statistics 13 ( 2 ): 435 – 525 With discussion .[Crossref], [Web of Science ®] , [Google Scholar]) evidenced the interest of the Projection Pursuit method thanks to the factorization of a density into a Gaussian component and some residual density in a context of Kullback–Leibler divergence maximisation.

In the present article, we introduce a new algorithm, and in particular, a test for the factorisation of a density estimated from an iid sample.     

基于消息"指纹"的等同测试方法研究

研究通信复杂性中的等同测试,提出基于消息“指纹”的概率测试方法,推导“错误匹配”概率计算公式;论述引入“随机性”不仅保证极低的通信复杂性,并使出现“错误匹配”的概率可忽略。     

高等学校预算项目与会计科目的匹配研究

随着预算管理和高等学校财务精细化管理的加强,国家对预算项目支出的用途、范围和内容都有严格的限定。财政部于2013年12月30日发布了财会〔2013〕30号关于印发《高等学校会计制度》的通知,对原有的会计科目进行了细分,以前所有的预算项目通过事业支出一个科目就能完成,现在需要通过不同的会计科目来完成。这就给预算项目支出的会计科目选择带来了一定的不便。文章就不同预算项目的支出如何更好地匹配会计科目进行探究,以便更好地反映经济活动的全貌,满足预算管理和会计核算工作的需要,更好地服务于高等学校的预算管理和会计核算工作。     

成果共享:当代中国政治哲学的核心范畴

发展成果由人民共享反映了人民群众主体性与社会发展的价值目标之间的必然联系,体现着当今中国政治哲学的价值追求,反映着中国特色社会主义的本质属性,是通往幸福中国的必由之路,因此,必须正确理解发展成果共享的深刻内涵,才能正确处理好社会发展中的一系列矛盾和若干关系。     

Assortative Matching and Search

In Becker's (1973) neoclassical marriage market model, matching is positively assortaive if types are complements: i.e., match output f(x, y) is supermodular in x and y. We reprise this famous result assuming time‐intensive partner search and transferable output. We prove existence of a search equilibrium with a continuum of types, and then characterize matching. After showing that Becker's conditions on match output no longer suffice for assortative matching, we find sufficient conditions valid for any search frictions and type distribution: supermodularity not only of output f, but also of log f_x and log f_xy. Symmetric submodularity conditions imply negatively assortative matching. Examples show these conditions are necessary.     

Directed Matching and Monetary Exchange

We develop a model of monetary exchange where, as in the random matching literature, agents trade bilaterally and not through centralized markets. Rather than assuming they match exogenously and at random, however, we determine who meets whom as part of the equilibrium. We show how to formalize this process of directed matching in dynamic models with double coincidence problems, and present several examples and applications that illustrate how the approach can be used in monetary theory. Some of our results are similar to those in the random matching literature; others differ significantly.     

On the Failure of the Bootstrap for Matching Estimators

Matching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap is, in general, not valid for matching estimators, even in the simple case with a single continuous covariate where the estimator is root‐N consistent and asymptotically normally distributed with zero asymptotic bias. Valid inferential methods in this setting are the analytic asymptotic variance estimator of Abadie and Imbens (2006a) as well as certain modifications of the standard bootstrap, like the subsampling methods in Politis and Romano (1994).