Estimation of the smaller and larger of two exponential location parameters

Assume independent random samples are drawn from two populations which are exponentially distributed with unknown location parameters and a common known scale parameter. We want to estimate the maximum and the minimum of the unknowo location paremeters. In this paper several estimators are proposed which are better than the natural estimations in terms of absolute bias and /or meaqn squared error.     

Bias Reduction through First-order Mean Correction, Bootstrapping and Recursive Mean Adjustment

Standard methods of estimation for autoregressive models are known to be biased in finite samples, which has implications for estimation, hypothesis testing, confidence interval construction and forecasting. Three methods of bias reduction are considered here: first-order bias correction, FOBC, where the total bias is approximated by the O(T^-1) bias; bootstrapping; and recursive mean adjustment, RMA. In addition, we show how first-order bias correction is related to linear bias correction. The practically important case where the AR model includes an unknown linear trend is considered in detail. The fidelity of nominal to actual coverage of confidence intervals is also assessed. A simulation study covers the AR(1) model and a number of extensions based on the empirical AR(p) models fitted by Nelson & Plosser (1982). Overall, which method dominates depends on the criterion adopted: bootstrapping tends to be the best at reducing bias, recursive mean adjustment is best at reducing mean squared error, whilst FOBC does particularly well in maintaining the fidelity of confidence intervals.     

Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient.     

Inference in the presence of ranking error in ranked set sampling

The author proposes inference techniques for ranked set sample data in the presence of judgment ranking errors. He bases his analysis on the models of Bohn & Wolfe (1994) and Frey (2007a, b), of which parameters are estimated by minimizing a distance measure. He then uses the fitted models to calibrate confidence intervals and tests. He shows the validity of his approach through simulation and illustrates its application through the construction of distribution‐free confidence intervals for the median area of apple tree leaves covered by a spray.     

跨文化交际障碍中的行为意识因素

鉴于国内的许多跨文化交际研究主要集中在纯语言的探讨和表层文化的分析上,试图从行为意识的角度出发,就思维定势、偏见意识和价值观念三大因素来分析跨文化交际中存在的障碍,从而使学习者排除跨文化交际的障碍,并从跨文化交流中获得益处。     

任务转换范式下情绪注意偏向

相对于其他信息来说,情绪信息往往会引起情绪障碍患者更多的注意并具有一种认知加工上的优先权。在注意实验中,与中性刺激相比,具有情绪意义的刺激更能吸引注意或占用注意资源从而引起注意偏向。通过转换代价和任务规则一致性效应两个指标阐述了任务转换范式下情绪障碍患者的情绪信息注意偏向加工机制,并指出这两种指标分别代表了个体在注意偏向中的两个不同的认知控制加工,为情绪障碍患者的情绪调节提供必要的依据。文中最后还指出了ERPs、f MRI新技术是未来任务转换范式下研究情绪与注意关系的新方向。     

投射偏差视角下的服务类品牌消费--以农村信息消费支付意愿为例

现将投射偏差模型框架引入服务类耐用品消费者均衡中,从理论上阐述投射偏差如何会导致消费者在服务类商品消费时无法达到效用最大化。研究采用实验和实地调研的方法,一共有251名人员参与了实验与调研,分析上网体验对于未来一年宽带的支付意愿影响。研究结果发现,人们在体验上网前后对于信息的认知状态有显著差异,没有上过网的人会基于当前的认知状态而低估未来一年宽带的效用,其支付意愿明显低于上过网的人,投射偏差在服务类耐用品的消费均衡中发挥了重要作用。     

中庸思维影响潜变量测量结果的验证

选取等效的新浪网、时光网、搜狐网和IMDb的口碑评价量表,以大学女生为调查对象,对6部热播电视剧进行口碑评价,得出中庸思维影响潜变量测评的结论.中庸思维的论证是通过研究被调查者内心已经有了一个特定打分倾向后对被测客体会如何打分来进行的,并通过计算条件均值的方法来验证.实证表明,被调查者内心有了一个特定打分倾向之后,依然会不自觉地偏向中心点给被测客体打分,验证了中国文化中中庸思维对潜变量测量的影响.另外,数据呈现出负偏现象,更多地是反映了被测客体的真实表现.     

Notes on estimation of the intraclass correlation under the AB/BA crossover trial

Under the AB/BA crossover trial, we focus our attention on estimation of the intraclass correlation in normal data. We develop both point and interval estimators in closed form for the intraclass correlation. We employ Monte Carlo simulation to study the performance of these estimators in a variety of situations. We note that the estimators developed here for the intraclass correlation remain valid even when there are possibly unexpected carry-over effects.     

Improved Estimates and Confidence Intervals for Regenerative Simulation

In regenerative simulation, one frequently requires an estimate or a confidence interval for the ratio of the means of the two components of a certain bivariate random quantity. Estimation of this ratio has been studied by many authors and most recently by Asmussen and Rydén(2010 Asmussen, S., Rydén, T. (2010). A note on skewness in regenerative simulation. Communications in Statistics—Simulation and Computation 40: 45–57.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). Here, we propose an estimate that performs better than the best of the known estimates. Our estimate is also lot simpler than the best known estimate.