数字时代中广告插画艺术的变革

人类进入数字时代后,先进的计算机技术不仅克服了文字数字化的难题,而且征服了比文字更复杂的声音、图像世界。主流与非主流插画开始应用到生活的各个方面,涉及到装修、时装、数码产品、互动媒体、电影、广告等等领域。面对正日益缩小的传统插画传播媒介间的差距,传统的传播者与受众之间的相互关系正面临巨大的变革。     

Darling–Erdős limit results for change-point detection in panel data

We wish to test the null hypothesis if the means of N panels remain the same during the observation period of length T. A quasi-likelihood argument leads to self-normalized statistics whose limit distribution under the null hypothesis is double exponential. The main results are derived assuming that the each panel is based on independent observations and then extended to linear processes. The proofs are based on an approximation of the sum of squared CUSUM processes using the Skorokhod embedding scheme. A simulation study illustrates that our results can be used in case of small and moderate N and T. We apply our results to detect change in the “corruption index”.     

A test for abrupt change in hazard regression models with Weibull baselines

We develop a likelihood ratio test for an abrupt change point in Weibull hazard functions with covariates, including the two-piece constant hazard as a special case. We first define the log-likelihood ratio test statistic as the supremum of the profile log-likelihood ratio process over the interval which may contain an unknown change point. Using local asymptotic normality (LAN) and empirical measure, we show that the profile log-likelihood ratio process converges weakly to a quadratic form of Gaussian processes. We determine the critical values of the test and discuss how the test can be used for model selection. We also illustrate the method using the Chronic Granulomatous Disease (CGD) data.     

A bayesian analysis of trend determination in economic time series

In this paper we provide a comprehensive Bayesian posterior analysis of trend determination in general autoregressive models. Multiple lag autoregressive models with fitted drifts and time trends as well as models that allow for certain types of structural change in the deterministic components are considered. We utilize a modified information matrix-based prior that accommodates stochastic nonstationarity, takes into account the interactions between long-run and short-run dynamics and controls the degree of stochastic nonstationarity permitted. We derive analytic posterior densities for all of the trend determining parameters via the Laplace approximation to multivariate integrals. We also address the sampling properties of our posteriors under alternative data generating processes by simulation methods. We apply our Bayesian techniques to the Nelson-Plosser macroeconomic data and various stock price and dividend data. Contrary to DeJong and Whiteman (1989a,b,c), we do not find that the data overwhelmingly favor the existence of deterministic trends over stochastic trends. In addition, we find evidence supporting Perron's (1989) view that some of the Nelson and Plosser data are best construed as trend stationary with a change in the trend function occurring at 1929.     

技能溢价源于技术进步偏向性吗？

 内生经济增长理论向来关注技术进步对经济增长的贡献,但现代研究却普遍忽视技术进步对异质性要素发展可能产生的偏向性影响,特别是技术进步能否呈现技能偏向性并引致不同类型劳动者报酬分化问题。本文利用双层嵌套型CES生产函数和非线性似不相关方法估计中国技能溢价水平,研究发现我国资本和劳动替代弹性小于1而技能和非技能劳动替代弹性大于1,技术进步偏向性及技能和非技能劳动的替代效应明显,利用技术进步偏向性模型模拟的数据与真实值无明显差异,印证技能溢价源于偏向型技术进步且偏向性效应不断强化。同时,回归方法检验结果也发现,技术进步偏向性对技能溢价正向效应显著,验证出我国技能溢价现象主要是源于技术进步偏向性作用的结果。     

A Novel Method to Calculate Mean Survival Time for Time-to-Event Data

In the analysis of time-to-event data, restricted mean survival time has been well investigated in the literature and provided by many commercial software packages, while calculating mean survival time remains as a challenge due to censoring or insufficient follow-up time. Several researchers have proposed a hybrid estimator of mean survival based on the Kaplan–Meier curve with an extrapolated tail. However, this approach often leads to biased estimate due to poor estimate of the parameters in the extrapolated “tail” and the large variability associated with the tail of the Kaplan–Meier curve due to small set of patients at risk. Two key challenges in this approach are (1) where the extrapolation should start and (2) how to estimate the parameters for the extrapolated tail. The authors propose a novel approach to calculate mean survival time to address these two challenges. In the proposed approach, an algorithm is used to search if there are any time points where the hazard rates change significantly. The survival function is estimated by the Kaplan–Meier method prior to the last change point and approximated by an exponential function beyond the last change point. The parameter in the exponential function is estimated locally. Mean survival time is derived based on this survival function. The simulation and case studies demonstrated the superiority of the proposed approach.     

Locally optimal invariant tests for change in level

The classical change point problem is considered, from the invariance point of view. Locally optimal invariant tests are derived for the change in level, when the initial level and the common variance are assumed to be unknown. The tests derived by Chernoff and Zacks (1964) and Gardner (1969), for the change in level, when variance is known, are shown to be locally optimal invariant tests.     

Bayesian Estimation of Change Point in Inverse Weibull Sequence

A sequence of independent lifetimes X ₁,…, X _m , X _m+1,…, X _n were observed from inverse Weibull distribution with mean stress θ₁ and reliability R ₁(t ₀) at time t ₀ but later it was found that there was a change in the system at some point of time m and it is reflected in the sequence after X _m by change in mean stress θ₁ and in reliability R ₂(t ₀) at time t ₀. The Bayes estimators of m, R ₁(t ₀) and R ₂(t ₀) are derived when a poor and a more detailed prior information is introduced into the inferential procedure. The effects of correct and wrong prior information on the Bayes estimators are studied.