论童年经验对苏童小说创作的影响

年轻作家苏童的小说引起人们的广泛关注。苏童生于江南古城苏州,有着孤独而寂寞的童年,对于祖辈生活过的扬中有着难以释怀的“故乡情结”,在体弱多病的日子里积聚了敏锐的观察力,同时有着丰富的想象力和独特的感受力,这一切都对其小说创作产生了深远的影响,促其形成“说故事”的创作风格,并以多种方式在其作品中体现出来。他的童年经验对其“红粉系列”、“枫杨树系列”、“香椿树街系列”以及“宫廷系列”等四类小说影响深远。     

生存困境的两种叙写——刘恒与池莉作品比较研究

刘恒、池莉的作品虽然都以凝重写实的风格,表现了人的生存艰难和生命卑微,但他们在叙述悲剧之源、叙事美学、作品的潜性主题等方面是不一样的。较之刘恒作品,池莉作品还包涵了执着的理想,而读者评论者往往忽略池莉作品中的潜性表现。     

茅盾作家论之流变刍议

在茅盾长达半个世纪的文学评论活动中,作家论型文学批评的创作为后世文学发展确立了一定的规范,具有鲜明的个人特色和深远的影响。通过对茅盾的七篇作家论及其创作背景的分析,不但可以辨析这种文体的演进过程,而且能够体现茅盾文学思想逐步溶入左翼主流文学的过程。     

A nonparametric inverse probability weighted estimation for functional data with missing response data at random

This paper considers the nonparametric inverse probability weighted estimation for functional data with missing response data at random. Under mild conditions, the asymptotic properties of the proposed estimation method are established. Based on the resampling method, the estimation of the asymptotic variance of the proposed estimator is obtained. Finally, the finite sample properties of the proposed estimation method are investigated via Monte Carlo simulation studies. A real data analysis is given to illustrate the use of the proposed method.     

Additive time-dependent hazard model with doubly truncated data

For doubly truncated data, i.e. the variables of interest are only observable if they lie in a certain random interval, an additive hazard model with time-dependent regression coefficients is investigated. Consistency and asymptotic normality are proven under mild assumptions. A simulation study investigates the finite sample properties and the influence of the truncation distribution on the estimation error. Finally, the method is applied to a doubly truncated data set of German companies, where the age at insolvency is of interest.     

Pseudo MLE for semiparametric transformation model with doubly truncated data

In this article, we consider the efficient estimation of the semiparametric transformation model with doubly truncated data. We propose a two-step approach for obtaining the pseudo maximum likelihood estimators (PMLE) of regression parameters. In the first step, the truncation time distribution is estimated by the nonparametric maximum likelihood estimator (Shen, 2010a) when the distribution function $K$ of the truncation time is unspecified or by the conditional maximum likelihood estimator (Bilker and Wang, 1996) when $K$ is parameterized. In the second step, using the pseudo complete-data likelihood function with the estimated distribution of truncation time, we propose expectation–maximization algorithms for obtaining the PMLE. We establish the consistency of the PMLE. The simulation study indicates that the PMLE performs well in finite samples. The proposed method is illustrated using an AIDS data set.