A STEPWISE CONFIDENCE INTERVAL PROCEDURE BASED ON AN ASYMMETRIC LOSS FUNCTION WITH APPLICATIONS TO TOXICOLOGICAL EVALUATION

The purpose of toxicological studies is a safety assessment of compounds (e.g. pesticides, pharmaceuticals, industrial chemicals and food additives) at various dose levels. Because a mistaken declaration that a really non-equivalent dose is equivalent could have dangerous consequences, it is important to adopt reliable statistical methods that can properly control the family-wise error rate. We propose a new stepwise confidence interval procedure for toxicological evaluation based on an asymmetric loss function. The new procedure is shown to be reliable in the sense that the corresponding family-wise error rate is well controlled at or below the pre-specified nominal level. Our simulation results show that the new procedure is to be preferred over the classical confidence interval procedure and the stepwise procedure based on Welch's approximation in terms of practical equivalence/safety. The implementation and significance of the new procedure are illustrated with two real data sets: one from a reproductive toxicological study on Nitrofurazone in Swiss CD-1 mice, and the other from a toxicological study on Aconiazide.     

Constrained Bayes and empirical Bayes estimation under random effects normal ANOVA model with balanced loss function

The paper develops constrained Bayes and empirical Bayes estimators in the random effects ANOVA model under balanced loss functions. In the balanced normal–normal model, estimators of the Bayes risks of the constrained Bayes and constrained empirical Bayes estimators are provided which are correct asymptotically up to O(m^-1)$\mathrm{O}(m^{-1})$, that is the remainder term is o(m^-1)$\mathrm{o}(m^{-1})$, m$m$ denoting the number of strata.     

Estimation of the exponential mean time to failure under a weighted balanced loss function

This paper considers estimation of a exponential mean time to failure using a loss function that reflects both goodness of fit and precision of estimation. The admissibility and inadmissibility of a class of linear estimators of the form are studied.     

朱淑贞事略考辨

朱淑贞是与李清照同时的女诗词家。传世作品多 ,技巧高妙 ,但在文学史上无显著地位。关于她的诸多误解中 ,婚姻悲剧迷雾重重。她的丈夫不是市井小民 ,而是无才无德之官吏。她不满家庭生活却没有桑濮之行。写男女幽会的《生查子》不是她的作品。“所适非偶”“匹偶非伦”“弗遂其志”“忧愁怨恨”不一定导致失志失节。她的作品“百不一存”是她个人损失也是中华民族文学宝库的损失     

用好新《会计法》治理会计信息失真

会计信息失真有其诸多内因,包括会计系统自身的局限性、会计制度建设滞后和实施机制不健全等,深刻分析这些内因,以找到治理的良方是我国会计界的一项重要任务。新《会计法》为治理会计信息失真提出了相应对策,它的颁布实施对治理会计信息失真具有重大意义。     

建立宏观均衡的微观基础

反通货膨胀政策会带来产量的损失,这是经济理论和中国经济实践已经充分证明了的.为此,我们必须加快企业体制和居民保障制度改革,为宏观经济调控创造一个适应的微观经济基础,保持经济的稳定发展.     

对国有资产中有形资产流失问题的探讨

国有资产中有形资产的流失存在动态流失与静态流失两种形式,动态流失因产权不清、管理不严或产权交易中规则不健全所致,具体又可分为经营性动态流失和人为性动态流失．静态流失与其是否进入市场交易有关．加强经济立法,完善和发展产权交易市场等可减少或避免国有有形资产的流失。     

Correlation in a Bayesian framework

The authors consider the correlation between two arbitrary functions of the data and a parameter when the parameter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p‐values and posterior probabilities of the null hypothesis in the one‐sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.     

通辽市近45年农业水资源变化分析

分析了通辽市近４５ 年降水、潜在蒸散及农田水分盈亏的变化,结果表明：年降水量在周期变化中具有减小的趋势,年降水量的稳定性增加,潜在蒸散波动上升。本世纪６０ 年代以来,春旱有所缓减,秋旱有所加剧     

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil

A heteroscedastic regression based on the odd log-logistic Marshall–Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.