中国农村公共服务评价体系研究

农村公共服务水平低下和不平衡是导致城乡差距日益扩大的重要影响因素之一。本文试图构建农村公共服务发展状况评价指标体系,并基于2006年的数据进行实证研究,给出了研究结果的进一步分析评价。     

Copula structure analysis

Summary.  We extend the standard approach of correlation structure analysis for dimension reduction of high dimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulas a correlation-like structure remains, but different margins and non-existence of moments are possible. After introducing the new concept and deriving some theoretical results we observe in a simulation study the performance of the estimators: the theoretical asymptotic behaviour of the statistics can be observed even for small sample sizes. Finally, we show our method at work for a financial data set and explain differences between our copula-based approach and the classical approach. Our new method yielear models also.     

Scrutinizing an algorithmic technique: the Bayes classifier as interested reading of reality

ABSTRACT

This paper outlines the notion of ‘algorithmic technique’ as a middle ground between concrete, implemented algorithms and the broader study and theorization of software. Algorithmic techniques specify principles and methods for doing things in the medium of software and they thus constitute units of knowledge and expertise in the domain of software making. I suggest that algorithmic techniques are a suitable object of study for the humanities and social science since they capture the central technical principles behind actual software, but can generally be described in accessible language. To make my case, I focus on the field of information ordering and, first, discuss the wider historical trajectory of formal or ‘mechanical’ reasoning applied to matters of commerce and government before, second, moving to the investigation of a particular algorithmic technique, the Bayes classifier. This technique is explicated through a reading of the original work of M. E. Maron in the early 1960 and presented as a means to subject empirical, ‘datafied’ reality to an interested reading that confers meaning to each variable in relation to an operational goal. After a discussion of the Bayes classifier in relation to the question of power, the paper concludes by coming back to its initial motive and argues for increased attention to algorithmic techniques in the study of software.     

Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples

This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained.     

The determinacy of the regression factor score predictor based on continuous parameter estimates from categorical variables

The estimation of population parameters of the continuous common factor model from categorical observed variables is meanwhile regularly performed. It is shown that the formula for the calculation of the determinacy of the regression factor score predictor from the estimated model parameters has to be adapted under these conditions. A method for the calculation of this determinacy from the model parameters of the continuous population factor model based on categorical variables is proposed and evaluated by means of simulated population data. It turns out that using the uncorrected formula can lead to serious overestimation of determinacy for categorical variables.     

The Bayes rule of the variance parameter of the hierarchical normal and inverse gamma model under Stein's loss

For the variance parameter of the hierarchical normal and inverse gamma model, we analytically calculate the Bayes rule (estimator) with respect to a prior distribution IG (alpha, beta) under Stein's loss function. This estimator minimizes the posterior expected Stein's loss (PESL). We also analytically calculate the Bayes rule and the PESL under the squared error loss. Finally, the numerical simulations exemplify that the PESLs depend only on alpha and the number of observations. The Bayes rules and PESLs under Stein's loss are unanimously smaller than those under the squared error loss.     

论会计管制与会计制度弹性

企业的契约本质决定了会计作为制造共同知识和控制机制在企业实施的必然性.信息不对称与机会主义等促使企业实施会计管制.囿于环境的复杂性、不完全信息和有限理性等,会计管制制度必须具有弹性.会计制度弹性空间作为公共区域,必然存在攫取租金的机会主义行为.计算并披露会计制度弹性信息有助于降低信息不对称,提高市场效率.     

Translation and factor analysis of structural models of Edinburgh Postnatal Depression Scale in Serbian pregnant and postpartum women – Web-based study

BackgroundThe Edinburgh Postnatal Depression Scale (EPDS) is well accepted for detecting symptoms of postnatal depression. The aim of this study was to examine psychometric properties and to evaluate structural models of the Serbian translation of EPDS in pregnant and postpartum women.MethodsThe original English version of the EPDS was translated into Serbian, and checked by means of back-translation. Data were collected via an anonymous online questionnaire posted on a Serbian website devoted to pregnancy topics. The study sample included 201 women (76 pregnant, 125 postpartum). The internal consistency of the scale was measured by Cronbach's α coefficient. Principal component analysis was used to determine scale dimensions while confirmatory factor analysis was used to evaluate model fit.FindingsCronbach α coefficient was 0.84 and 0.83 in pregnant and postpartum women, respectively, which indicated good internal consistency of the Serbian EPDS. Three dimensions of the scale were revealed in both groups of women. Goodness of fit indices described good and excellent model in pregnant and postpartum women, respectively. High level of depression symptoms (score ≥13) was recorded in 27.6% and 24.8% (p > 0.05) of pregnant and postpartum women, respectively. Moderate level of depression symptoms (score 10–12) was recorded in 21.1% and 16.8% (p > 0.05) of pregnant and postpartum women, respectively.ConclusionThe Serbian translation of the EPDS showed good consistency and good model characteristics in pregnant and postpartum women. However, cut-off values, sensitivity and specificity of the scale should be determined in the further studies with more representative samples of women.