Linearity,symmetry, and equidistance in semantic differential scales for measuring images of self and images of others

ABSTRACT

Violations of linearity, symmetry, and equidistance of scale points in semantic differential scales may be due to respondents failing to figure out antonyms, to a positivity bias, or to respondents curtailing their reading the options. Multiple correspondence analysis on data provided by a randomized between-subjects experiment (split-ballot), using a web survey of 537 German residents, shows that bipolar semantic differential scales allow for linear measurement and conceal no positivity bias, and that using not suitable adjective pairs in semantic differential scales destroys symmetry.     

Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

Progressive censoring with fixed censoring times

In this paper, we revisit the progressive Type-I censoring scheme as it has originally been introduced by Cohen [Progressively censored samples in life testing. Technometrics. 1963;5(3):327–339]. In fact, original progressive Type-I censoring proceeds as progressive Type-II censoring but with fixed censoring times instead of failure time based censoring times. Apparently, a time truncation has been added to this censoring scheme by interpreting the final censoring time as a termination time. Therefore, not much work has been done on Cohens's original progressive censoring scheme with fixed censoring times. Thus, we discuss distributional results for this scheme and establish exact distributional results in likelihood inference for exponentially distributed lifetimes. In particular, we obtain the exact distribution of the maximum likelihood estimator (MLE). Further, the stochastic monotonicity of the MLE is verified in order to construct exact confidence intervals for both the scale parameter and the reliability.     

Tempered Mittag-Leffler Lévy processes

In this article, we introduce tempered Mittag-Leffler Lévy processes (TMLLP). TMLLP is represented as tempered stable subordinator delayed by a gamma process. Its probability density function and Lévy density are obtained in terms of infinite series and Mittag-Leffler function, respectively. Asymptotic forms of the tails and moments are given. A step-by-step procedure of the parameters estimation and simulation of sample paths is given. We also provide main results available for Mittag-Leffler Lévy processes (MLLP) and some extensions which are not available in a collective way in a single article. Our results generalize and complement the results available on Mittag-Leffler distribution and MLLP in several directions. Further, the asymptotic forms of the moments of the first-exit times of the TMLLP are also discussed.     

多边贸易体制下中国发展中国家地位问题研究——基于历史、现实与规范的多维考察

当前,发展中国家地位问题受到国际社会的高度关注,已成为世界贸易组织改革中的主要讨论议题。然而,现行世界贸易组织多边规则体系中并没有关于“发展中国家地位”的清晰界定,“自我认定”的方式正遭受一些国家的挑战。发展中国家地位和特殊与差别待遇条款密切相关,世界贸易组织规则体系中涵盖的155项特殊与差别待遇条款为发展中国家的国内政策提供了一定的灵活性,尽管多数为“最佳努力条款”。中国的发展中国家地位兼具身份和契约的双重属性,部分发达国家迫使中国放弃发展中国家地位,本质上旨在继续维持其在国际经济秩序中的主导地位。虽然中国的发展正处于“强起来”的第三阶段,但仍须坚持发展中国家地位不动摇。放弃发展中国家地位并不等于将获得发达国家的自动接纳,相反,还会影响到在其他国际组织和国际事务中的角色扮演,中国的发展离不开广大发展中国家的支持。当然,坚持发展中国家地位并不等于需要和其他发展中成员享受完全一致的差别待遇,在后续谈判中,中国可以保持一定的灵活性。在国际治理中,中国也将继续为国际社会的发展提供解决方案,树立负责任大国形象。     

Confidence intervals,significance values,maximum likelihood estimates,etc. sharpened into Occam’s razors

Abstract

Confidence sets, p values, maximum likelihood estimates, and other results of non-Bayesian statistical methods may be adjusted to favor sampling distributions that are simple compared to others in the parametric family. The adjustments are derived from a prior likelihood function previously used to adjust posterior distributions.     

几类全微分方程问题的求解定理

利用全微分方程的条件，给出一类微分方程的积分因子及通解公式，得出一类全微分方程中未知函数所满足的二阶线性微分方程，获得未知函数及全微分方程的通解。     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.     

Statistical and Combinatorial Aspects of Comparative Genomics*

Abstract. This document presents a survey of the statistical and combinatorial aspects of four areas of comparative genomics: gene order based measures of evolutionary distances between species, construction of phylogenetic trees, detection of horizontal transfer of genes, and detection of ancient whole genome duplications.     

国外教师期望效应研究进展与当代教育启示

教师期望效应是教师对学生的期望在学生的未来发展中得到证实的现象,它反映了教师对学生的态度会影响学生发展的方向和程度,开展该现象的研究对教师观念的改变和学生的健康发展均有重要意义。对教师期望效应的种类、理论模型及国外的相关研究进行了介绍,探讨了其对教育现实的一些重要启示。