On moment indeterminacy of the Benini income distribution

The Benini distribution is a lognormal-like distribution generalizing the Pareto distribution. Like the Pareto and the lognormal distributions it was originally proposed for modeling economic size distributions, notably the size distribution of personal income. This paper explores a probabilistic property of the Benini distribution, showing that it is not determined by the sequence of its moments although all the moments are finite. It also provides explicit examples of distributions possessing the same set of moments. Related distributions are briefly explored.     

The value of rescheduling functionality within standard MRP packages

One of the basic functions of an MRP system is to issue rescheduling messages that urge the planner tospeed up or slow down open orders. It seems in practice that these messages are not used at all by planners. This is mostly due to the inaccuracy of MRP, that more or less ignores safety time, safety stocks and lotsize flexibility in the calculation of reschedule-in messages. Reschedule-out messages are usually ignored because planners do not see the value of the message. Other reasons for not adhering to rescheduling messages are a lack of maintenance of MRP parameters or simply the wrong use of the MRP function. In the future, MRP rescheduling functionality will be used even less than today, due to the changing role of MRP within the planning framework. With the uprise of finite capacity scheduling packages, MRP is being pushed one level upward in the planning hierarchy. This means that rescheduling functionalities for the short term will become completely obsolete in MRP systems.     

Engendering Response: Professional Gesture and the Assessment of Eyesight in Optometry Consultations

Many of the procedures undertaken within healthcare require specialized forms of participation that may be unfamiliar, even disturbing, to patients or clients. The practitioner has to encourage and enable participation in the investigation in an appropriate fashion while preserving the structure and integrity of the procedure. In this article, we consider optometry and the deployment of a vision test, known as subject refraction, that provides data to help determine the characteristics of any corrective lens that may be required by clients. The procedure's ability to establish robust and reliable data relies upon the optometrist's ability to encourage the client to respond to a series of stimuli without consideration or reflection. That is, the client is required to produce an unwitting response—conduct that might be considered nonsymbolic rather than symbolic. In this article, we also consider the optometrist's talk and bodily comportment during subjective refraction and how it serves to shape and determine the quality of the client's response and participation, and in turn to produce reliable test results.     

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.     

加拿大采矿业注重培养技术工人

采矿业面临着内外因素困扰,前进路上步履艰难,外部矿产品价格低迷,内部作业条件与环境恶劣.在这种严峻的情况下,矿业要千方百计克服矿产品开采与加工中的各种困难(挖掘深度加大、矿种品位降低、环保要求严格等等),除了提高生产效率、降低成本,最重要的是加快人才培养,改善人力资源管理.要达到上述目的,依靠传统办法,无法实现.所幸的是,进入21世纪后,以微电子技术为核心的科技进步为此提供了可靠的技术保证.这种需要与可能相结合就会诱导出一场变革,即技术革新,其中矿山自动化是这场变革中的主角.     

Tests of serial independence based on Kendall's process

The authors propose new rank statistics for testing the white noise hypothesis in a time series. These statistics are Cramér‐von Mises and Kolmogorov‐Smirnov functionals of an empirical distribution function whose mean is related to a serial version of Kendall's tau through a linear transform. The authors determine the asymptotic behaviour of the underlying serial process and the large‐sample distribution of the proposed statistics under the null hypothesis of white noise. They also present simulation results showing the power of their tests.     

Inference in model-based cluster analysis

A new approach to cluster analysis has been introduced based on parsimonious geometric modelling of the within-group covariance matrices in a mixture of multivariate normal distributions, using hierarchical agglomeration and iterative relocation. It works well and is widely used via the MCLUST software available in S-PLUS and StatLib. However, it has several limitations: there is no assessment of the uncertainty about the classification, the partition can be suboptimal, parameter estimates are biased, the shape matrix has to be specified by the user, prior group probabilities are assumed to be equal, the method for choosing the number of groups is based on a crude approximation, and no formal way of choosing between the various possible models is included. Here, we propose a new approach which overcomes all these difficulties. It consists of exact Bayesian inference via Gibbs sampling, and the calculation of Bayes factors (for choosing the model and the number of groups) from the output using the Laplace–Metropolis estimator. It works well in several real and simulated examples.