论企业组织创新风险

企业组织创新伴随着巨大风险 ,导致创新行为的失败。风险蛰伏在以人为中心、以组织结构为中心和组织流程为中心的组织创新内容中 ,通过创新动机、战略、整合和速度等创新行为要素表现出来。造成创新风险的原因在于企业组织创新动因机理的复杂性、运行过程的动态不平衡性以及组织创新环境与条件的变动性诸方面。     

《伙计》的现征艺术

象征是马拉默德惯用的手法之一 ,也是构成其代表作《伙计》艺术成就的一个重要方面。在这部作品中 ,马拉默德将象征应用于结构、情节、背景三个方面 ,使其在人物塑造、气氛营造、主题揭示及作品意义的深化等方面发挥了重要作用。本文从结构象征、情节象征、背景象征三个方面探讨了《伙计》高超的象征艺术     

剑溪堂刻本《书经》考述

剑溪堂刻本《书经》为近年在徽州地区发现的一种《尚书》新版本。根据其书口、版式、字体、用纸、内封面以及避讳等情况综合判断,该书刊行于明神宗万历年间,与北图藏元明间宗文书堂刻本《书集传音释六卷》同出一个版本系统。它的出现对于认识《书经》乃至整个《尚书》的流变史有其重要意义。在蔡沈集传《书经》普遍流行六册、七册线装本的情况下,三册毛装本无疑还具有较强的版本认识价值。     

Living Arrangements, Employment Status, and the Economic Well-Being of Mothers: Evidence from Brazil, Chile, and the U.S

Using data from Brazil, Chile, and the U.S., we estimate country specific models of household income that characterize mothers according to their marital status, living arrangement, and employment status. We assess the predicted economic well-being of each type of mother relative to a benchmark of married mothers in the same country, and at various points in the income distribution. We find dramatic cross-country differences in the distribution of mothers across categories, but few differences in each type's relative economic status. In all three countries and at all points in the income distribution, mothers who are the only adults in their households have the lowest levels of predicted income, while married mothers—followed closely by cohabitors—have the highest levels.     

On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

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.     

中古史书勘误三则

中华书局点校本中古史书是我们研究中古史料的最易得、最权威的本子。由于史书涉及内容广泛，在标点和校勘中难免存在一些可商榷之处。笔者谨将日前所见中古史书点校中的问题，列出三则，敬请方家指正。     

A Semi-parametric Regression Model with Errors in Variables

Abstract.  In this paper, we consider a partial linear regression model with measurement errors in possibly all the variables. We use a method of moments and deconvolution to construct a new class of parametric estimators together with a non-parametric kernel estimator. Strong convergence, optimal rate of weak convergence and asymptotic normality of the estimators are investigated.     

A semi-parametric approach to robust parameter design

Parameter design or robust parameter design (RPD) is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic. An essential component of RPD involves the assumption of well estimated models for the process mean and variance. Traditionally, the modeling of the mean and variance has been done parametrically. It is often the case, particularly when modeling the variance, that nonparametric techniques are more appropriate due to the nature of the curvature in the underlying function. Most response surface experiments involve sparse data. In sparse data situations with unusual curvature in the underlying function, nonparametric techniques often result in estimates with problematic variation whereas their parametric counterparts may result in estimates with problematic bias. We propose the use of semi-parametric modeling within the robust design setting, combining parametric and nonparametric functions to improve the quality of both mean and variance model estimation. The proposed method will be illustrated with an example and simulations.     

左思风力之成因初探

西晋诗人左思的诗风在西晋文坛上独树一帜，称之为“左思风力”，前人对此有较多地论述，然而就诗风形成的原因却缺乏深入地探究。本文试图从社会时代背景、家庭因素、性格特征三个方面对此加以分析，旨在能够更好地把握左思其人及其诗风。