Estimation of a quadratic regression functional using the sinc kernel

We use the sinc kernel to construct an estimator for the integrated squared regression function. Asymptotic normality of the estimator at different rates is established, depending on whether the regression function vanishes or not.     

Simple inference in multinomial and ordered logit

This paper provides some simple methods of interpreting the coefficients in multinomial logit and ordered logit models. These methods are summarized in Propositions concerning the magnitudes, signs, and patterns of partial derivatives of the outcome probabilities with respect to the exogenousvariables. The paper also provides an empirical example illustrating the use of these Propositions.     

Covid-19 and the euthanasia of interest rates: A critical assessment of central bank policy in our times

We compare the New Keynesian and Austrian explanations for low interest rates in the light of the Corona crisis. From a New Keynesian perspective low interest rates are the result of structural changes in the society and the economy as well as the cyclical downswing triggered by the Corona pandemic. In contrast, from the perspective of Austrian economic theory, interest rates have been pushed down on trend by central banks for a long time to stimulate growth, with the global financial crisis of 2007/08 and the Corona crisis of 2020 acting as powerful accelerators of the euthanasia of interest. New Keynesian theory would suggest that interest rates can be adjusted upward again when conditions change, without creating economic and financial disturbances. Against this, Austrian theory finds that central banks have backed themselves into a corner by creating persistent low-interest expectations.     

震后人群常见的心理困扰及应对策略

创伤后应激障碍又称延迟性心因性反应,是灾难性事件发生后在灾区及灾区之外的人们中普遍存在的一种心理应激反应.它不仅有滞后性,持续时间长,而且可能伴随当事人终生,必须引起社会的广泛重视.而要消除心理"余震",除介入及时外,必须做好打持久战的心理准备.对汶川大地震也是如此.为此,必须充分发挥传媒的社会稳定功能,确保信息准确,为灾区群众提供心理屏障;还要建立社会支持系统.帮助丧失亲朋者顺利度过悲哀历程,学会面对事实,寻求新的生活目标.此外,探索震后心理调适方法,鼓励震后人群进行自我情绪调整也十分必要.     

灾后志愿者心理援助体系初探

汶川大地震后,志愿者作为灾难现场的目击者和救援的参与者,不可避免地处于应激状态之中.与直接受灾者相比,志愿者在应激源和中介两个方面存在差异,如应急源的时程不同、对灾害的认知评价和应对方式上的差异等.针对这些特点,对灾后志愿者的心理援助工作应该全程、全面和系统地展开.根据志愿者行动时程,可建立筛查、预仿、监测、跟踪等与心理援助相结合的灾后志愿者心理援助体系.     

对地震中丧亲大学生的心理干预探析

对因5·12汶川大地震丧亲的大学生给予心理干预的目的在于帮助他们度过正常的悲哀反应期，帮助他们正视痛苦，充分地哀悼逝去的亲人以及寻找到新的生活目标。整个干预过程必须遵循个体化与共感原则、多方面参与系统性原则、全程监护原则，并恰当运用心理疏导技术和悲伤处理技术，以帮助地震中丧亲的大学生重新燃起生活的希望，坚定面对未来生活的勇气和信心，促进其心理重建。     

Model‐based linear clustering

The authors propose a profile likelihood approach to linear clustering which explores potential linear clusters in a data set. For each linear cluster, an errors‐in‐variables model is assumed. The optimization of the derived profile likelihood can be achieved by an EM algorithm. Its asymptotic properties and its relationships with several existing clustering methods are discussed. Methods to determine the number of components in a data set are adapted to this linear clustering setting. Several simulated and real data sets are analyzed for comparison and illustration purposes. The Canadian Journal of Statistics 38: 716–737; 2010 © 2010 Statistical Society of Canada     

Seemingly unrelated reduced-rank regression model

Reduced-rank regression models proposed by Anderson [1951. Estimating linear restrictions on regression coefficients for multivariate normal distributions. Ann. Math. Statist. 22, 327–351] have been used in various applications in social and natural sciences. In this paper we combine the features of these models with another popular, seemingly unrelated regression model proposed by Zellner [1962. An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J. Amer. Statist. Assoc. 57, 348–368]. In addition to estimation and inference aspects of the new model, we also discuss an application in the area of marketing.     

ARMA MODELS REALIZATION AND IMPULSE RESPONSES

A parallel is made between the role played by covariances in the determination of auto-regressive models and the role played by impulse responses in the determination of ARMA models.

Auto-regressive models are known to maximize the Burg-entropy under covariance constraints. Auto-regressive-moving-average models give the maximum of the Burg-entropy among processes sharing the same covariances and impulse responses up to a certain lag. Such models are constructed by iterative or algebraic methods under the different constraints.

A new recursive method of identification of the order of an ARMA model is also developed, based on the generalized reflection coefficients.