Testing for Serial Independence: Beyond the Portmanteau Approach

Portmanteau tests are typically used to test serial independence even if, by construction, they are generally powerful only in presence of pairwise dependence between lagged variables. In this article, we present a simple statistic defining a new serial independence test, which is able to detect more general forms of dependence. In particular, differently from the Portmanteau tests, the resulting test is powerful also under a dependent process characterized by pairwise independence. A diagram, based on p-values from the proposed test, is introduced to investigate serial dependence. Finally, the effectiveness of the proposal is evaluated in a simulation study and with an application on financial data. Both show that the new test, used in synergy with the existing ones, helps in the identification of the true data-generating process. Supplementary materials for this article are available online.     

Robust Bayesian nonlinear mixed‐effects modeling of time to positivity in tuberculosis trials

Early phase 2 tuberculosis (TB) trials are conducted to characterize the early bactericidal activity (EBA) of anti‐TB drugs. The EBA of anti‐TB drugs has conventionally been calculated as the rate of decline in colony forming unit (CFU) count during the first 14 days of treatment. The measurement of CFU count, however, is expensive and prone to contamination. Alternatively to CFU count, time to positivity (TTP), which is a potential biomarker for long‐term efficacy of anti‐TB drugs, can be used to characterize EBA. The current Bayesian nonlinear mixed‐effects (NLME) regression model for TTP data, however, lacks robustness to gross outliers that often are present in the data. The conventional way of handling such outliers involves their identification by visual inspection and subsequent exclusion from the analysis. However, this process can be questioned because of its subjective nature. For this reason, we fitted robust versions of the Bayesian nonlinear mixed‐effects regression model to a wide range of TTP datasets. The performance of the explored models was assessed through model comparison statistics and a simulation study. We conclude that fitting a robust model to TTP data obviates the need for explicit identification and subsequent “deletion” of outliers but ensures that gross outliers exert no undue influence on model fits. We recommend that the current practice of fitting conventional normal theory models be abandoned in favor of fitting robust models to TTP data.     

马克思理论视阈中的“现实的人”——以《德意志意识形态》为文本考察

现实的人是马克思新哲学的出发点和落脚点，同时也是马克思对整个思想史上各种“片面人”的颠覆性阐释，是唯物史观与唯心史观和经验论决裂的标识。它不同于性恶论或性善论或既无善亦无恶论，也不同于黑格尔的“绝对精神”的人，更不同于费尔巴哈的“类”。与黑格尔思想及其青年黑格尔派和费尔巴哈等人思想交锋的过程中，马克思分别通过以所有制为轴线动态考察历史发展和以分工为轴线静态考察社会的结构性存在两条线索来阐释“现实的人”的内涵，并以生产工具为红线，对资本主义社会下“现实的人”的静态结构和动态发展予以微观透视。由此，按照唯物史观的基本立场、观点和方法来说，以经济决定政治、政治决定文化的序列构成的结构性存在来解释人才是马克思所谓的“现实的人”。     

Self-exciting threshold models for time series of counts with a finite range

In this article, an integer-valued self-exciting threshold model with a finite range based on the binomial INARCH(1) model is proposed. Important stochastic properties are derived, and approaches for parameter estimation are discussed. A real-data example about the regional spread of public drunkenness in Pittsburgh demonstrates the applicability of the new model in comparison to existing models. Feasible modifications of the model are presented, which are designed to handle special features such as zero-inflation.     

Completing the Circuit: Routine,Reflection, and Ethical Consumption

Efforts to explain why some people incorporate ethical concerns into everyday shopping for food and household goods, while many do not, have so far left significant variation in “ethical consumption” unexplained. Seeking to move beyond explanations that rely mainly on differences in consumers' social class, gender, and political engagement, I draw on concepts associated with “practice theory” to argue that ethical consumption is closely tied to people's willingness and ability to spend time, while shopping, on distinct activities associated with breaking old routines and establishing new ones. The central insight of practice theory is that most consumption is the product of unconscious routine. And it is precisely because consciously departing from routine is, according to my study, a fundamentally time‐consuming process, that lack of time emerges as a crucial obstacle to translating abstract ethical concerns into concrete action as a consumer.     

Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time‐Series and Intervention Analysis

In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time‐series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time‐series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two‐month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time‐series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014.     

真实性学习理念下的教学方法及实践应用

本文分享了作者在美国研修期间亲身经历的体现真实性学习理念的三种教学方法与活动:同伴教学、跨时空对话、视频制作。通过真实再现纽约州立大学奥斯威戈分校研修课堂精彩片段,分析教学方法与原理,并探讨在国内高校尤其是教师教育课堂的应用途径。     

Quantile Regression for Location‐Scale Time Series Models with Conditional Heteroscedasticity

This paper considers quantile regression for a wide class of time series models including autoregressive and moving average (ARMA) models with asymmetric generalized autoregressive conditional heteroscedasticity errors. The classical mean‐variance models are reinterpreted as conditional location‐scale models so that the quantile regression method can be naturally geared into the considered models. The consistency and asymptotic normality of the quantile regression estimator is established in location‐scale time series models under mild conditions. In the application of this result to ARMA‐generalized autoregressive conditional heteroscedasticity models, more primitive conditions are deduced to obtain the asymptotic properties. For illustration, a simulation study and a real data analysis are provided.     

建构一个新的城乡一体化分析框架：机会平等视角

对城乡一体化的现有研究或采用经济学视角,或采用制度学视角,而很少采用机会平等视角。研究认为:不论是经济资源配置还是制度和政策制定,都要视对城乡机会平等的影响如何,来判断其是否促进城乡一体化进程。机会平等是城乡一体化的本质属性。当然,机会是复杂、多样的,可以划分为基本生存机会、中层机会和高层机会,与此同时,平等也可以划分为形式平等和实质平等。在推进不同类型机会平等上,城乡一体化表现出不同的进度。该分析框架可以更好地分析我国城乡一体化进程(包括地区城乡一体化进程)。     

Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.