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.     

Product partition latent variable model for multiple change-point detection in multivariate data

The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.     

脊波导宽频带电磁参数测试技术

针对高损耗介质材料电磁参数的宽频带测试问题,提出了利用脊波导进行测试的新方法,建立了电磁参数测试系统,并采用TRL技术进行了系统校准。该方法仅用3个波段的脊波导即可覆盖2.0～18.0GHz宽频带范围内的电磁参数测试,具有频带宽、体积小、测试精确度高等优点。     

无理数e在电路基本理论中出现的物理意义

对无理数e在电路分析中出现的几个典型例子作了分析讨论，明确指出：由1／e决定的特征常数可以在时间分布上和空间分布上，把一个按指数规律非均匀变化的问题，用一个等效的均匀变化的问题来表示；可以反映初始变化率与最终稳定值之间的联系；可以更深刻地反映某些物理过程的本质特征。     

非英语专业学生英语学习策略使用频率的研究

本调查以内蒙古工业大学非英语专业二年级的109名学生为样本,采取观察和问卷形式,考察非英语专业学生使用何种学习策略以及学习策略的使用频率.结果表明六种学习策略中,非英语专业学生最常用的策略是补偿策略,最不常用的策略是记忆策略.最后,作者指出本文的教学实践意义:即学习策略的培训应融于课堂教学中,其应用应体现于课堂教学活动中     

Assessing goodness-of-fit of categorical regression models based on case-control data

Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets.     

TESTING SPHERICITY UNDER A MIXTURE MODEL

The robustness of Mauchly's sphericity test criterion when sampling from a mixture of two multivariate normal distributions is studied. The distribution of the sphericity test criterion when the sample covariance matrix has a non-central Wishart density of rank one is derived in terms of Meijer's G-functions; its distribution under the mixture model is then deduced. The robustness is studied by computing actual significance levels of the test under the mixture model using the critical values under the usual normal model.     

分析Chiral分层媒质特性的一般方法(英文)

提出了一套系统方法用于求解任意导体片位于界面的Chiral分层媒质的谐振频率,衰减因子和电磁场分布。文中的分析是在Fourier变换域的并矢格林函数和矩阵分析的基础上来进行的,给出的公式的最大价值在于它提供了求解Chiral分层媒质问题的方法论。