Analyzing multiple vector autoregressions through matrix-variate normal distribution with two covariance matrices

Abstract

This article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method.     

对马尔可夫测度的研究

给出了马尔可夫测度定义，讨论了马尔可夫测度的一部分性质     

A NOTE ON EVANESCENT PROCESSES

This note examines the connection between μ-invariant measures for the transition function of a continuous-time Markov chain and those of its q-matrix, Q. The major result establishes a necessary and aufficient condition for a convergent μ-invariant measure for Q to be μ-inhant for the minimal transition function, P, under the assumption that P is honest. This corrects Theorem 6 of Vere-Jones (1969) and the first part of Corollary 1 of Pollett (1986), both of which assert that the above conclusion holds in the absence of this condition. The error was pointed out by E.A. van Doom (1991) and the counterexample which be presented provides the basis for the present arguments. In determining where the error occurred in the original proof, we are able to identify a simple sufficient condition for μ-invariance.     

从不同价值领域看中国传统价值观

对不同价值领域间关系的定位与评判是反映人们价值观的一个重要维度。中国传统价值观在道德价值与非道德价值领域、家庭生活与政治生活领域、道德价值与超道德的神圣价值领域、不同文化领域之间的关系上都表现出一元论的倾向。我们应立足于领域分离、价值多元的现代背景对其进行反思 ,以构建有中国特色的价值观念体系     

指数级数的增长性和值分布

本文研究了随机狄里克莱级数 在随机变量序列{Xn}独立（可不同分布）以及满足等条件时的增长性以及值分布,得到了一些新的结果.     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

Bayesian analysis of discrete time warranty data

Summary.  The analysis of warranty claim data, and their use for prediction, has been a topic of active research in recent years. Field data comprising numbers of units returned under guarantee are examined, covering both situations in which the ages of the failed units are known and in which they are not. The latter case poses particular computational problems for likelihood-based methods because of the large number of feasible failure patterns that must be included as contributions to the likelihood function. For prediction of future warranty exposure, which is of central concern to the manufacturer, the Bayesian approach is adopted. For this, Markov chain Monte Carlo methodology is developed.     

On a Dualization of Graphical Gaussian Models: A Correction Note

Abstract.  We correct two proofs concerning Markov properties for graphs representing marginal independence relations.     

俄汉语认知域中的转喻与隐喻连续体现象——以俄汉语“手”的认知为例

语言中的基本范畴词是人们认识世莽的基础，在此基础上人们通过转喻、隐喻来认知更抽象的概念和事物。俄汉语中的“рука——手”同属基本范畴词，具有很强的转喻：隐喻能力。通过手部动作认知、情绪认知、场景认知、权势认知、身体结构认知等方面研究俄汉语认知域中转喻与隐喻的交互作用在词汇层面的连续体关系，将有助于从实证的角度对比分析俄汉语转喻和隐喻思维模式的异同，探求造成两个民族认知差异的文化因素。