Joint modeling of linear degradation and failure time data with masked causes of failure under simple step-stress test

In this paper, we propose a method to model the relationship between degradation and failure time for a simple step-stress test where the underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to induce failure experimentally and a tampered failure rate model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates of the model parameters are obtained through the expectation–maximization algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real-world example is analysed to illustrate the application of the proposed methods.     

Estimation of the Moment Generating Function

A number of statistical problems use the moment generating function (mgf) for purposes other than determining the moments of a distribution. If the distribution is not completely specified, then the mgf must be estimated from available data. The empirical mgf makes no assumptions concerning the underlying distribution except for the existence of the mgf. In contrast to the nonparametric approach provided by the empirical mgf, alternative estimators can be formed based on an assumed parametric model. Comparison of these approaches is considered for two parametric models; the normal and a one parameter gamma. Comparison criteria are efficiency and empirical confidence interval coverage. In general the parametric estimators outperform the empirical mgf when the model is correct. The comparisons are extended to underlying models which are two component mixtures from the distributional family assumed by the parametric estimators. Under the mixture models the superiority of the parametric estimator depends upon the model, value of the argument of the mgf, and the comparison criterion. The empirical mgf is the better estimator in some cases.     

Moral Utility Theory: Understanding the motivation to behave (un)ethically

Moral Utility Theory provides an integrative framework for understanding the motivational basis of ethical decision making by modeling it as a process of subjective expected utility (SEU) maximization. The SEUs of ethical and unethical behavioral options are proposed to be assessed intuitively during goal pursuit, with unethical conduct emerging when the expected benefits of moral transgressions outweigh the expected costs. A key insight of the model is that any factors that increase the value of a goal—including incentives, framings, and mindsets—can motivate misbehavior by increasing the SEU of unethical conduct. Although Moral Utility Theory emphasizes the automatic and habitual nature of most SEU appraisals, it also describes a mechanism for initiating the deliberative moral reasoning process: the experience of moral uncertainty. Moral uncertainty is proposed to occur when the SEUs of ethical and unethical behaviors are similar in magnitude, thereby activating the behavioral inhibition system and motivating the allocation of attentional resources toward the decision process. This framework bridges the gap between affective and cognitive perspectives on ethical decision making by identifying automatic evaluations as a central driver of moral decisions while also specifying when and how moral reasoning processes are initiated. By combining dual-process models of morality with well-validated principles from the science of motivation, Moral Utility Theory provides theoretical parsimony and formal modeling potential to the study of ethical decision making. The framework also suggests practical strategies—from employee selection and training to goal setting and compensation systems—for encouraging ethical behavior in organizations.     

A mixture model using likelihood‐based and Bayesian approaches for identifying responders and non‐responders in longitudinal clinical trials

A longitudinal mixture model for classifying patients into responders and non‐responders is established using both likelihood‐based and Bayesian approaches. The model takes into consideration responders in the control group. Therefore, it is especially useful in situations where the placebo response is strong, or in equivalence trials where the drug in development is compared with a standard treatment. Under our model, a treatment shows evidence of being effective if it increases the proportion of responders or increases the response rate among responders in the treated group compared with the control group. Therefore, the model has flexibility to accommodate different situations. The proposed method is illustrated using simulation and a depression clinical trial dataset for the likelihood‐based approach, and the same depression clinical trial dataset for the Bayesian approach. The likelihood‐based and Bayesian approaches generated consistent results for the depression trial data. In both the placebo group and the treated group, patients are classified into two components with distinct response rate. The proportion of responders is shown to be significantly higher in the treated group compared with the control group, suggesting the treatment paroxetine is effective. Copyright © 2014 John Wiley & Sons, Ltd.     

最优司法判决结果的博弈解读——兼及法律方法的可操作性

最优判决结果应为司法活动永恒的最高追求.从博弈论的视角解读,最优的司法判决结果应当是一个合法的、具有可接受性的而且实现了利益最大化的判决结果,亦即纳什均衡基础之上帕累托最优的实现.为达到这一目标,法官在视角选择时应站在"局内的局外人"的立场,而在实际操作时采取"无为的独裁者"的策略.通过这一问题的分析还表明,法律方法应具有可操作性,并且应将其作为法律方法研究进一步深入拓展的突破点与基本目标之一.     

The importance of taxes in entrepreneurial decisions: an analysis of practicing physicians’ behavior

An irrational strong importance of taxes in an individual’s decision-making behavior is one of the most popular assumptions about the behavioral effects of taxation. However, empirical research about this phenomenon is rare. In a study of German physicians, this paper analyzes whether tax aspects are over weighted in entrepreneurial decision-making. Furthermore, factors that may influence the irrational decision-making behavior of actors are analyzed. As research method, a conjoint analysis is used that permits measurement of the relative importance of tax aspects in decisions. The first result of the study is that the majority of the respondents (practicing physicians) misestimate their own marginal tax rate. The main result of the study is that––in comparison to the neoclassical model of rational maximization of consumption utility––most of the respondents overweight tax aspects. No evidence can be found for any relationship between indicators of a possible tax aversion (e.g., low satisfaction with the tax system) and attention to tax aspects in the decisions analyzed.

On the equivalence between descending bid auctions and first price sealed bid auctions

Bidding the same price in descending bid auctions and in first price sealed bid auctions is equivalent to expected utility maximizing behavior, and this is equivalent to dynamically consistent bidding. The claim that, in strategic form, descending bid and first price sealed bid auctions are the same game is thus shown to be false, since the mapping from strategies to payoffs is not the same for the two auction forms.     

A comparison of different procedures for principal component analysis in the presence of outliers

Principal component analysis (PCA) is a popular technique that is useful for dimensionality reduction but it is affected by the presence of outliers. The outlier sensitivity of classical PCA (CPCA) has caused the development of new approaches. Effects of using estimates obtained by expectation–maximization – EM and multiple imputation – MI instead of outliers were examined on the artificial and a real data set. Furthermore, robust PCA based on minimum covariance determinant (MCD), PCA based on estimates obtained by EM instead of outliers and PCA based on estimates obtained by MI instead of outliers were compared with the results of CPCA. In this study, we tried to show the effects of using estimates obtained by MI and EM instead of outliers, depending on the ratio of outliers in data set. Finally, when the ratio of outliers exceeds 20%, we suggest the use of estimates obtained by MI and EM instead of outliers as an alternative approach.     

公司治理结构与股利分配动机--基于代理成本和利益侵占的分析

本文以我国上市公司为对象,从公司治理结构安排的角度,系统研究2001年管理层出台新政策后公司的股利分配动机.结果表明,降低代理成本假说和利益侵占假说都在不同程度地发挥作用,集团控股公司适合降低代理成本假说;而对于政府控制公司,用利益侵占假说解释其股利分配动机更为恰当.我们进一步发现,针对我国特殊的股权结构特征及流通特征,现金股利在中国资本市场中具有"双刃剑"特征.     

股息红利所得税的收入再分配效应研究

 内容提要：股息红利所得税（以下简称股利所得税）是我国政府调节证券市场运行的重要政策工具。然而,在当今我国社会收入差距不断扩大的态势下,对股利所得税收入再分配效应进行深入分析,更具有重要的现实意义。本文力图从平均税率累进性和税前税后基尼系数的角度,在理论方面分析了股利所得税的收入再分配效应;在实证方面,利用中国2000—2008年城镇居民调查数据进行了实证检验。通过实证分析发现：第一,股利所得税平均税率在城镇不同收入组之间都具有累进性;第二,城镇股利所得税的税后基尼系数小于税前基尼系数,即股利所得税具有缩小收入差距的作用;第三,股利所得税的收入再分配效应因时期不同而存在差异;第四,降低股利所得税率导致股利所得税的收入再分配效应减弱。