Bayesian life test planning for the Weibull distribution with given shape parameter

This paper describes Bayesian methods for life test planning with Type II censored data from a Weibull distribution, when the Weibull shape parameter is given. We use conjugate prior distributions and criteria based on estimating a quantile of interest of the lifetime distribution. One criterion is based on a precision factor for a credibility interval for a distribution quantile and the other is based on the length of the credibility interval. We provide simple closed form expressions for the relationship between the needed number of failures and the precision criteria. Examples are used to illustrate the results.Received: October 2002 / Revised: March 2004     

Input- and Output-Oriented Technical Efficiency of Ukrainian Collective Farms, 1989–1992: Bayesian Analysis of a Stochastic Production Frontier Model

We propose estimation of a stochastic production frontier model within a Bayesian framework to obtain the posterior distribution of single-input-oriented technical efficiency at the firm level. All computations are carried out using Markov chain Monte Carlo methods. The approach is illustrated by applying it to production data obtained from a survey of Ukrainian collective farms. We show that looking at the changes in single-input-oriented technical efficiency in addition to the changes in output-oriented technical efficiency improves the understanding of the dynamics of technical efficiency over the first years of transition in the former Soviet Union.     

基于数据融合的自来水浊度检测方法

为了提高流动电流仪(SCM)对自来水浊度检测的精度,文章提出了一种基于神经网络数据融合技术的数据处理方法。该方法可以消除测量中的原水流量、供电电源波动、絮凝剂浓度、温度等干扰量对流动电流仪的影响,提高了测量的精度。     

基于递归对角神经网络自适应均衡算法的研究

阐述了神经网络自适应均衡算法的基本原理,提出了一种基于递归对角神经网络的自适应均衡算法,推导了算法的迭代公式,进行了计算机仿真。结果表明,随着传输信号信噪比的增加,稳态剩余误差减小,误码率降低。     

人工神经网络在住房销售率预测中的应用

住房销售率是开发商最为关心的问题之一。多种不确定因素的影响为准确的预测销售率带来困难。人工神经网络能够模拟人脑的思维过程,建立多个变量的非线性模型,从而为准确预测住房销售率提供了一种新思路。     

Monitoring recessions: A Bayesian sequential quickest detection method

Monitoring business cycles faces two potentially conflicting objectives: accuracy and timeliness. To strike a balance between these dual objectives, we propose a Bayesian sequential quickest detection method to identify turning points in real time with a sequential stopping time as a solution. Using four monthly indexes of real economic activity in the United States, we evaluated the method’s real-time ability to date the past five recessions. The proposed method identified similar turning-point dates as the National Bureau of Economic Research (NBER), with no false alarms, but on average, it dated peaks four months faster and troughs 10 months faster relative to the NBER announcement. The timeliness of our method is also notable compared to the dynamic factor Markov-switching model: the average lead time was about five months when dating peaks and two months when dating troughs.     

Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S_b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions.     

Societal preferences for fertility treatment in Australia: a stated preference discrete choice experiment

Objective: To investigate preferences for fertility treatment from the Australian general population with the aims of calculating the willingness to pay in tax contribution for attributes (characteristics) that make up treatment and for an “ideal” fertility treatment program. We also assessed whether willingness-to-pay varies by the relationship status or sexual orientation of the patient.

Methods: A stated preference discrete choice experiment was administered to a panel of 801 individuals representative of the Australian general population. Seven attributes of fertility treatment under three broad categories were included: outcome, process, and cost. Attributes were identified through published literature, focus group discussions, expert knowledge, and a pilot study. A Bayesian fractional experimental design was used, and data analysis was performed using a generalized multinomial logit model. Further analyses included interaction terms and latent class modeling.

Results: Six of the seven attributes influenced the choice of a treatment program. Under process attributes, individuals preferred: continuity of care of clinic staff, where patients are seen by the same doctor but different nurses at each visit; “alternative” treatments being offered to all patients; and onsite clinic counseling and peer-support groups. Personalization and tailoring of the treatment journey were not important. Among outcome attributes, the improved success rate of having a baby per cycle and significant side-effects were considered important. Cost of treatment also influenced the choice of treatment program. Individual preferences for fertility treatment were not associated with patients’ relationship status or sexual orientation. Latent class modeling revealed sub-groups with distinct fertility treatment preferences.

Conclusion: This study provides important insights into the attributes that influence the preferences of fertility treatment in Australia. It also estimates socially-inclusive willingness-to-pay values in tax contributions for an “ideal” package of treatment. The results can inform economic evaluations of fertility treatment programs.     

企业网络组织协同竞争的理论与效应解析

竞争与合作相统一的协同竞争已成为企业网络竞争战略发展的必然趋势。通过对企业网络组织协同竞争研究脉络的梳理，可构建协同竞争研究的评析架构。其理论演进是：以系统思维作为理论逻辑的基点，以合作竞争为行动策略，以价值创造作为网络协同竞争的本质属性；在实践效应上，协同竞争具有提升竞争优势的特征，而博弈模型对协同效应发挥着解析工具的作用。     

Optimal mechanisms for siting noxious facilities

We study Bayesian mechanism design in the context of the siting of noxious facilities. Under incomplete information, we characterize optimal mechanisms facilitating the siting and cost sharing of the facility. These mechanisms are allocatively and Pareto efficient. However, it appears that transfers occur when the good is not provided. This result is due to the weakening of the incentive notion to Bayesian–Nash equilibrium and to the balanced budget condition. This phenomenon disappears if the setting is perfectly symmetric.