A future for statistics education-we will do more with less

Demands for statistics are increasing but so are demands for colleges and universities to become more "efficient." Some innovations in statistics teaching will allow us to do more with less, but we will have to make choices about where to invest our time. We can also work harder at competing for scarce resources.     

Supersmooth testing on the sphere over analytic classes

We consider the nonparametric goodness-of-fit test of the uniform density on the sphere when we have observations whose density is the convolution of an error density and the true underlying density. We will deal specifically with the supersmooth error case which includes the Gaussian distribution. Similar to deconvolution density estimation, the smoother the error density the harder is the rate recovery of the test problem. When considering nonparametric alternatives expressed over analytic classes, we show that it is possible to obtain original separation rates much faster than any logarithmic power of the sample size according to the ratio of the regularity index of the analytic class and the smoothness degree of the error. Furthermore, we show that our fully data-driven statistical procedure attains these optimal rates.     

In Memoriam: Simon Kuznets, 1901-1985

The profession of statistics has adopted too narrow a definition of itself. As a consequence, both statistics and statisticians play too narrow a role in policy formation and execution. Broadening that role will require statisticians to change the curriculum they use to train and develop their own professionals and what they teach nonstatisticians about statistics. Playing a proper role will require new research from statisticians that combines our skills in methods with other techniques of social scientists.     

A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments

A multi-stratum design is a useful tool for industrial experimentation, where factors that have levels which are harder to set than others, due to time or cost constraints, are frequently included. The number of different levels of hardness to set defines the number of strata that should be used. The simplest case is the split-plot design, which includes two strata and two sets of factors defined by their level of hardness-to-set. In this paper, we propose a novel computational algorithm which can be used to construct optimal multi-stratum designs for any number of strata and up to six optimality criteria simultaneously. Our algorithm allows the study of the entire Pareto front of the optimization problem and the selection of the designs representing the desired trade-off between the competing objectives. We apply our algorithm to several real case scenarios and we show that the efficiencies of the designs obtained present experimenters with several good options according to their objectives.     

Elephants and Ivory

Counting elephants ought to be easy. It is not. Counting elephants lost to poaching is even harder. But, without knowledge of both, how can we know whether banning the sale of ivory is helping to save elephants? Bob Burn explains the problems.     

A guided walk Metropolis algorithm

The random walk Metropolis algorithm is a simple Markov chain Monte Carlo scheme which is frequently used in Bayesian statistical problems. We propose a guided walk Metropolis algorithm which suppresses some of the random walk behavior in the Markov chain. This alternative algorithm is no harder to implement than the random walk Metropolis algorithm, but empirical studies show that it performs better in terms of efficiency and convergence time.     

On the detection of changes in autoregressive time series I. Asymptotics

Various test statistics are discussed which can be used for detecting changes in the parameters of an autoregressive time series. In this first part of our study, the limiting behavior of the test statistics is derived under the null hypothesis of no change as well as under alternatives. In a forthcoming second part of our investigation, these asymptotic results will be compared to some corresponding bootstrap procedures, and a small simulation study will be conducted.     

利用菲德模型测量教育投资的外溢效应

一、教育投资经济效益的理论探讨在现代社会中 ,教育的作用和影响是多方面的 ,教育既具有经济职能又具有社会职能。教育投资的经济效益是教育发挥其经济职能的表现。教育投资的经济效益 (简称教育的经济效益 ,是指通过教育再生产出一定数量和质量的人才 ,进而提高社会劳动生产率 ,促进国民经济的增长 ,在其增长总额中抵偿用于教育和培养的全部经费之后的余额。对于教育投资的经济效益的计量 ,由于教育的经济效益的复杂性及理论研究的欠缺 ,至今没有一个理想的统一标准。目前 ,具有代表性的几种计量方法主要有 :(1) )舒尔茨的余数分析法。舒…     

A note on homogeneity tests of covariance matrices

In this note we propose two procedures for testing homogeneity of co-variance matrices that are both extensions of Hartley's (1940) test for equality of variances. The first is a two-stage procedure where the first step is a simple test for equality of the largest eigenvalues, and corresponding eigenvectors, of the covariance matrices. The second is based on projection pursuit and seems harder to apply in practice.     

Operational Research changes: tales from a parallel universe

Operational research and statistics share many common features. A review of the historical development and of some current dilemmas in operational research is given, in the belief that the narrative will fulfil a wider purpose by causing statisticians to reflect on related aspects of the evolution of their own subject in a rapidly changing environment.     

AN EXCLUSIVE REGRESSORS BINARY MIXTURE MODEL WITH AN APPLICATION TO LABOUR SUPPLY

This paper suggests a new type of mixture regression model, in which each mixture component is explained by its own regressors. Thus, the dependent variable can be driven by one of several unobservable explanatory mechanisms, each of which has its own distinct variables. An extension of the simulated annealing algorithm is introduced to fit this general mixture model. The paper also suggests a new technique for estimating the covariance matrix of estimators in a mixture model. Finally, empirical studies of a labour supply example show that our proposed model can perform much better than conventional logistic or mixture models.     

Testing inference in variable dispersion beta regressions

The class of beta regression models proposed by Ferrari and Cribari-Neto [Beta regression for modelling rates and proportions, Journal of Applied Statistics 31 (2004), pp. 799–815] is useful for modelling data that assume values in the standard unit interval (0, 1). The dependent variable relates to a linear predictor that includes regressors and unknown parameters through a link function. The model is also indexed by a precision parameter, which is typically taken to be constant for all observations. Some authors have used, however, variable dispersion beta regression models, i.e., models that include a regression submodel for the precision parameter. In this paper, we show how to perform testing inference on the parameters that index the mean submodel without having to model the data precision. This strategy is useful as it is typically harder to model dispersion effects than mean effects. The proposed inference procedure is accurate even under variable dispersion. We present the results of extensive Monte Carlo simulations where our testing strategy is contrasted to that in which the practitioner models the underlying dispersion and then performs testing inference. An empirical application that uses real (not simulated) data is also presented and discussed.     

Changing from Single to Separate Records: A Case Study from the University of Nevada,Reno

The University of Nevada, Reno Libraries made the decision in early 2012 to convert its bibliographic records from a single record approach, with multiple formats of a title on one bibliographic record, to a separate record approach, where each format receives its own record. This decision was several years in the making, as it was a change that would potentially require breaking apart more than 20,000 records. It would involve numerous staff from different departments and would require adjustments for all staff who worked with library users. This article will discuss the factors that pushed the UNR Libraries to make this decision to split its records and the challenges technical services staff faced in managing the project. The authors will present the different procedures developed for splitting monographic and serial records and the different tools that were used to make the process work: Millennium (especially the ERM and Global Update modules), MarcEdit, and Serials Solutions' MARC Updates service.     

Effect of choice complexity on design efficiency in conjoint choice experiments

Conjoint choice experiments have become a powerful tool to explore individual preferences. The consistency of respondents' choices depends on the choice complexity. For example, it is easier to make a choice between two alternatives with few attributes than between five alternatives with several attributes. In the latter case it will be much harder to choose the preferred alternative which is reflected in a higher response error. Several authors have dealt with this choice complexity in the estimation stage but very little attention has been paid to set up designs that take this complexity into account. The core issue of this paper is to find out whether it is worthwhile to take this complexity into account in the design stage. We construct efficient semi-Bayesian D-optimal designs for the heteroscedastic conditional logit model which is used to model the across respondent variability that occurs due to the choice complexity. The degree of complexity is measured by the entropy, as suggested by Swait and Adamowicz (2001). The proposed designs are compared with a semi-Bayesian D-optimal design constructed without taking the complexity into account. The simulation study shows that it is much better to take the choice complexity into account when constructing conjoint choice experiments.     

Algorithms for restricted least absolute value estimation

We present a concise summary of recent progress in developing algorithms for restricted least absolute value (LAV) estimation (i. e. ?₁ approximation subject to linear constraints). The emphasis is on our own new algorithm, and we provide some numerical results obtained with it.     

A NOTE ON THE NUMBER OF DUST PARTICLES IN A SAMPLE OF AIR-BORNE MINE DUST

A stochastic model is proposed for the distribution of the number of particles in a sample of air-borne mine dust, and it, is shown that in special circumstances the distribution will be that of a Poisson variate.
I am indebted to Professor Bartlett for drawing my attention to his own more general result and to the referee for the suggestion that led to the unconditional result of Section 4.     

What is Mentoring?

What is mentoring? Is it just a buzz word or is this really valuable? How can mentoring help one to grow and advance personally and professionally? How and where does one even begin? Many of us have these questions. In this article, I will share my perspective and provide some reflections on these questions based on my own personal and professional journey.     

Discipline-Specific Literature Bases: A View of the APS Model

Abstract

Librarians see the large quantities of literature and the complete writing/publishing/world as a complete system. Changes to one piece (e.g., making publishing or reading electronic) will not fundamentally change the process. The pieces of the system are there, not for technological reasons, but for reasons of authority, validation, and self-correction in the process of scholarly communication. Electronic publishing will cause great changes, but the changes will not eliminate roles that now exist. The changes will be to enhance our abilities to better do that which we do now, whether that be to edit, review, referee, write, or manage the information flow.     

Reflections on the UK National Lottery

Gambling in Britain has been transformed by the National Lottery. The small pink ticket from the newsagent's electronic outlet offers temptation of wealth beyond the dreams of avarice. John Haigh examines a bet that, statistically, not one of our readers will live to win.     

The Probability Distribution for the Number of Successes in Independent Trials

The number of successes S in n independent trials is one of the classic distributions in statistics. When the probability of success p is constant, S has the binomial distribution with parameters n and p. Distributional properties of S in the homogeneous case are well known, but they are considerably harder to establish when p varies. A brief historical review is undertaken to highlight some of the more important results obtained over the past 50 years. In spite of the progress made, there are still some important open problems concerning stochastic comparisons for S that deserve to be solved!