On the estimation of the extreme value and normal distribution parameters based on progressive type-II hybrid-censored data

A progressive hybrid censoring scheme is a mixture of type-I and type-II progressive censoring schemes. In this paper, we mainly consider the analysis of progressive type-II hybrid-censored data when the lifetime distribution of the individual item is the normal and extreme value distributions. Since the maximum likelihood estimators (MLEs) of these parameters cannot be obtained in the closed form, we propose to use the expectation and maximization (EM) algorithm to compute the MLEs. Also, the Newton–Raphson method is used to estimate the model parameters. The asymptotic variance–covariance matrix of the MLEs under EM framework is obtained by Fisher information matrix using the missing information and asymptotic confidence intervals for the parameters are then constructed. This study will end up with comparing the two methods of estimation and the asymptotic confidence intervals of coverage probabilities corresponding to the missing information principle and the observed information matrix through a simulation study, illustrated examples and real data analysis.     

二度价格歧视情形下垄断厂商收益最大化条件

采用定量分析方法研究垄断厂商采用二度价格歧视条件下的收益变化，给出了收益最大化的条件，并给出了垄断厂商可能获得的最大收益。有关结论对厂商和消费者都有重要意义     

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.     

A family of skew distributions with mode-invariance through transformation of scale

Recently, a new family of skew distributions was proposed using a specific class of transformation of scale, in which the normalizing constant remains unchanged and unimodality is readily assured. In this paper, we introduce the mode invariance in this family, which allows us to easily study certain properties, including monotonicity of skewness, and incorporate various favorable properties. The entropy maximization for a skew distribution is discussed. A numerical study is also conducted.     

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.     

基于多属性决策的未动用油气储量评价方法研究

未动用油气储量综合评价是油田确定区块开发序列,降低开发风险、提高开发效益的关键问题之一,多属性决策为解决该问题提供了理论与方法基础。提出一种集结决策者或专家打分与均方差最大化的组合赋权法,并结合加权算术平均算子构建了基于多属性决策的未动用油气储量评价方法。依据未动用油气储量特征,分析选择11个指标构成评价指标体系。最后,通过中国西北某区26个已探明未动用区块的实证分析,说明该方法合理有效。     

以社会主义生产目的为目标的两大部类最优投资分配——以马克思扩大再生产理论为基础

文章以马克思扩大再生产理论为基础建立了一个最优控制模型,通过最优条件的变换得到了两大部类投资比例的最优算法。该算法表明,在没有发生革命性变革的情况下,两大部类投资比例是常数,这意味着文章推导出的最优解具有普遍意义。     

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.     

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.

试论高等院校财务管理目标

高校财务管理应随着外部环境的变化而制定新的管理目标和具体管理目标。在当前的环境下,应以价值最大化作为高校财务管理的总目标,实现筹资、投资、成本、分配管理的具体化。