Weighted Integral Test Statistics and Components of Smooth Tests of Fit

This paper considers families of statistics for testing the goodness-of-fit of various parametric models such as the normal, exponential or Poisson. Each family consists of weighted integrals over the squared modulus of some measure of deviation from the parametric model, expressed by means of an empirical transform of the data. Letting the rate of decay of the weight function tend to infinity, each test statistic, after a suitable rescaling, approaches a limit that is closely connected to the first non-zero component of Neyman's smooth test for the parametric model.     

正态格拉布斯统计量的近似分布

在正态总体 N(μ,σ~2)下,推导出样本均值与样本最大值、最小值之差同标准差之比的这类统计量(亦即格拉布斯(Grubbs)统计量)的大样本近似分布,从而给出了大样本情形格拉布斯统计量的上侧分位数的一种简单、直接的计算方法,扩展了这类重要检验统计量的应用范围。     

改革开放以来党的素质文化思想生成逻辑

改革开放以来,党推进中华民族文明素质发展的文化思想生成逻辑清晰地展现出：建构新型文化教育观念,以提高国民素质为根本宗旨的生成起点;坚持人本立场,以提高中华民族素质为根本目的的内在价值生成;弘扬“真、善、美”,以提升中华民族素质新文明观念和审美水平为目标的内涵生成;建设社会主义核心价值体系与践行社会主义核心价值观,以推进中华民族文明素质发展的新型价值体系与实践标准的生成。在探索中华民族文明素质教育路径与方法中形成实践观等全面生成的脉络,由此形成了党推进中华民族文明素质发展的文化内涵、价值取向和行为准则、实现路径与方法相互联系的素质文化范式。     

Inferential Theory for Factor Models of Large Dimensions

This paper develops an inferential theory for factor models of large dimensions. The principal components estimator is considered because it is easy to compute and is asymptotically equivalent to the maximum likelihood estimator (if normality is assumed). We derive the rate of convergence and the limiting distributions of the estimated factors, factor loadings, and common components. The theory is developed within the framework of large cross sections (N) and a large time dimension (T), to which classical factor analysis does not apply. We show that the estimated common components are asymptotically normal with a convergence rate equal to the minimum of the square roots of N and T. The estimated factors and their loadings are generally normal, although not always so. The convergence rate of the estimated factors and factor loadings can be faster than that of the estimated common components. These results are obtained under general conditions that allow for correlations and heteroskedasticities in both dimensions. Stronger results are obtained when the idiosyncratic errors are serially uncorrelated and homoskedastic. A necessary and sufficient condition for consistency is derived for large N but fixed T.     

Parameter Estimation for Hidden Markov Models with Intractable Likelihoods

Approximate Bayesian computation (ABC) is a popular technique for analysing data for complex models where the likelihood function is intractable. It involves using simulation from the model to approximate the likelihood, with this approximate likelihood then being used to construct an approximate posterior. In this paper, we consider methods that estimate the parameters by maximizing the approximate likelihood used in ABC. We give a theoretical analysis of the asymptotic properties of the resulting estimator. In particular, we derive results analogous to those of consistency and asymptotic normality for standard maximum likelihood estimation. We also discuss how sequential Monte Carlo methods provide a natural method for implementing our likelihood‐based ABC procedures.     

Exact distribution of the convolution of negative binomial random variables

In this note, we derive the exact distribution of S by using the method of generating function and BELL polynomials, where S = X₁ + X₂ + ??? + X_n, and each X_i follows the negative binomial distribution with arbitrary parameters. As a particular case, we also obtain the exact distribution of the convolution of geometric random variables.     

The generalized transmuted-G family of distributions

We introduce a new class of continuous distributions called the generalized transmuted-G family which extends the transmuted-G class. We provide six special models of the new family. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Rényi and Shannon entropies, order statistics and probability weighted moments are derived. The estimation of the model parameters is performed by maximum likelihood. The flexibility of the proposed family is illustrated by means of three applications to real data sets.     

The exponentiated transmuted-G family of distributions: Theory and applications

In this paper, a new family of continuous distributions called the exponentiated transmuted-G family is proposed which extends the transmuted-G family defined by Shaw and Buckley (2007). Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Rényi and Shannon entropies, and order statistics are derived. Some special models of the new family are provided. The maximum likelihood is used for estimating the model parameters. We provide the simulation results to assess the performance of the proposed model. The usefulness and flexibility of the new family is illustrated using real data.     

公立医疗机构民营化的路径选择与风险判断

自20世纪90年代后期以来,中国政府采用了渐进性的策略推动了公立医疗机构的转制与改革,民营医疗机构的数量得以大幅度攀升。尽管公立医疗机构民营化改革在增加医疗卫生资源供给、提高医疗机构运作效率与缓解政府财政负担方面显现了独到的优势,但是民营化的不良后果亦日渐暴露出来,尤其是民营化改革所内蕴的风险更是引起了社会各界的关注。本文在界定公立医疗机构民营化的内涵与可行性的基础上阐述了公立医疗机构民营化的实现路径,进而从医疗机构与患者的供需关系出发建构医疗服务提供体系,厘清医疗机构、患者与医疗保险机构等参与主体自身的内在风险因素,以及各参与主体间制约关系失衡时所引发的风险,包括新垄断风险、监管风险、软约束风险与社会公平风险等,力求全面地诠释公立医疗机构民营化的风险及其发生的机理。     

玄学与科学之“殊途”与“同归”——以中日建筑民俗的比较研究为视点

从中日建筑民俗的变迁中,体味两种文化背景所铸造的民俗特征及所构建的文化空间,有助于了解一个民族的文化精神。从＂龙＂、＂气＂等风水理念之差别入手,对中日建筑民俗之间的差异进行分析,展示出我国两大风水流派＂形势宗＂与＂理气宗＂的吉凶观念;对照证实主义的科学方法和自然生态景观理论,剖析两国建筑民俗变迁、发展的要义及其与现代社会发展的关系。＂风水＂在中日建筑文化中都有着长久的传承,应该给＂风水＂一个生存的空间,留待进一步研究和感悟。民俗中的＂玄学＂部分,其中有些神秘文化现象虽至今仍未能以现代科学加以解释,但其与＂科学＂并非一定存在矛盾,只是目前还没有找到两者的切合点,在当今多元化的社会中,不妨令其共存。