Oracle model selection for correlated data via residuals

This paper concerns model selection for autoregressive time series when the observations are contaminated with trend. We propose an adaptive least absolute shrinkage and selection operator (LASSO) type model selection method, in which the trend is estimated by B-splines, the detrended residuals are calculated, and then the residuals are used as if they were observations to optimize an adaptive LASSO type objective function. The oracle properties of such an adaptive LASSO model selection procedure are established; that is, the proposed method can identify the true model with probability approaching one as the sample size increases, and the asymptotic properties of estimators are not affected by the replacement of observations with detrended residuals. The intensive simulation studies of several constrained and unconstrained autoregressive models also confirm the theoretical results. The method is illustrated by two time series data sets, the annual U.S. tobacco production and annual tree ring width measurements.     

卜辞中所见商代诸神的权能

本文通过对甲骨刻辞资料的断代爬梳、整理,在继承前人研究成果的基础之上,分别探讨了王卜辞与非王卜辞中所见商人诸神的权能,分析了诸神施行权能的方式,并勾勒出商代诸神权能变迁大势.     

殷墟小屯南地甲骨中的截锯卜旬卜骨

殷墟小屯村南出土的截锯卜旬卜骨共有35例,从其行款、钻凿形态等方面看,其与村南的无一、无二类卜辞更接近,从其左、右肩胛骨上的字形、书风看,也与康丁时代的无一类、无二类卜辞一致。     

从甲骨文看殷周时代的田猎文化

我国殷、周时代的文字在其形体构造上一般都具有十分鲜明的历史文化的具象性。当时由于殷、周宗法社会的特定需求,田猎与国家的政治、军事紧密结合在一起,形成了一种特有的田猎文化。文章通过一系列有关的甲骨文形义关系的分析研究,描述了由古汉字文化具象所反映出来的殷、周田猎之种种情况;作者亦对某些未识的甲骨文提出了自己的考释性意见。     

“王若曰”新考

“王若曰”是先秦典籍和金文材料中比较常见的词语。对该词语的释义，目前仍未取得一致意见。通过对金文、简牍和传世典籍中的相关资料进行考察和梳理，可知“王若曰”不是王一般的谈话，而主要是指王命，语感在强调其庄严性。此外，学者以往举出的殷墟甲骨文中“王若曰”的例证并不可靠，从现有材料来看，“王若曰”可能是周人的说法。     

Variable selection in heterogeneous panel data models with cross-sectional dependence

This paper studies the Bridge estimator for a high-dimensional panel data model with heterogeneous varying coefficients, where the random errors are assumed to be serially correlated and cross-sectionally dependent. We establish oracle efficiency and the asymptotic distribution of the Bridge estimator, when the number of covariates increases to infinity with the sample size in both dimensions. A BIC-type criterion is also provided for tuning parameter selection. We further generalise the marginal Bridge estimator for our model to asymptotically correctly identify the covariates with zero coefficients even when the number of covariates is greater than the sample size under a partial orthogonality condition. The finite sample performance of the proposed estimator is demonstrated by simulated data examples, and an empirical application with the US stock dataset is also provided.