Numerical solution of optimal allocation problems in stratified sampling under box constraints

Modern sampling designs in survey statistics, in general, are constructed in order to optimize the accuracy of estimators such as totals, means and proportions. In stratified random sampling a variance minimal solution was introduced by Neyman and Tschuprov. However, practical constraints may lead to limitations of the domain of sampling fractions which have to be considered within the optimization process. Special attention on the complexity of numerical solutions has to be paid in cases with many strata or when the optimal allocation has to be applied repeatedly, such as in iterative solutions of stratification problems. The present article gives an overview of recent numerical algorithms which allow adequate inclusion of box constraints in the numerical optimization process. These box constraints may play an important role in statistical modeling. Furthermore, a new approach through a fixed point iteration with a finite termination property is presented.     

‘Zealotry or Nostalgic Regret’?1 Women Leaders in Technical and Further Education in Australia: Agents of Change,Entrepreneurial Educators or Corporate Citizens?

Education has been restructured in many Western post‐industrial nation states during the 1990s. The Australian Technical and Further Education sector (TAFE) has been particularly susceptible to discourses of responsiveness to the market and the new entrepreneuralism. This article explores how women have been repositioned in contradictory and ambiguous ways as the new entrepreneurial middle managers by existing and emergent discourses that circulated in and through TAFE organizations. In turn, it points to how discourses of change management and client responsiveness took on particular readings within specific institutional and professional cultures of the eight Technical and Further Education institutions (TAFEs). At the same time, the restructuring that arose from the corporatization of TAFE, in a highly gendered process, through the twin strategies of marketization and the new managerialism produced new possibilities for individual women educators who moved up into middle management. Yet these individual women were positioned within highly masculinist ‘neo‐corporate bureaucratic cultures’ that co‐opted their passion for the capacity of education to make a difference and incorporated these new entrepeneurial work identities.     

Going Public: Networking Globally and Locally*

Abstract Rural sociologists figure prominently in the move towards public sociology. The paper takes up Michael Burawoy's call for public sociology and discusses what rural sociologists have to offer to publics and how we stand to gain as a discipline in working with publics. The paper argues that rural sociologists' ability to adopt a cosmopolitan view while negotiating the complexities of global/local processes provides a useful theoretical stance for doing public sociology. Methodologically, both feminist methods and various approaches to networks can guide us as we do public sociology. Then, the paper provides two examples of recent efforts to do public sociology with a women's community group in Sri Lanka in response to the tsunami and with the Pennsylvania Women's Agricultural Network to illustrate the possibilities and limitations of working with networks. In conclusion, the paper addresses opportunities for doing public sociology, the challenges we face as we go public, and future work that is needed to develop theoretically and methodologically strong public rural sociology.     

Block‐threshold‐adapted Estimators via a Maxiset Approach

We study the maxiset performance of a large collection of block thresholding wavelet estimators, namely the horizontal block thresholding family. We provide sufficient conditions on the choices of rates and threshold values to ensure that the involved adaptive estimators obtain large maxisets. Moreover, we prove that any estimator of such a family reconstructs the Besov balls with a near‐minimax optimal rate that can be faster than the one of any separable thresholding estimator. Then, we identify, in particular cases, the best estimator of such a family, that is, the one associated with the largest maxiset. As a particularity of this paper, we propose a refined approach that models method‐dependent threshold values. By a series of simulation studies, we confirm the good performance of the best estimator by comparing it with the other members of its family.     

Non-parametric Curve Estimation by Wavelet Thresholding with Locally Stationary Errors

An important aspect in the modelling of biological phenomena in living organisms, whether the measurements are of blood pressure, enzyme levels, biomechanical movements or heartbeats, etc., is time variation in the data. Thus, the recovery of a 'smooth' regression or trend function from noisy time-varying sampled data becomes a problem of particular interest. Here we use non-linear wavelet thresholding to estimate a regression or a trend function in the presence of additive noise which, in contrast to most existing models, does not need to be stationary. (Here, non-stationarity means that the spectral behaviour of the noise is allowed to change slowly over time). We develop a procedure to adapt existing threshold rules to such situations, e.g. that of a time-varying variance in the errors. Moreover, in the model of curve estimation for functions belonging to a Besov class with locally stationary errors, we derive a near-optimal rate for the -risk between the unknown function and our soft or hard threshold estimator, which holds in the general case of an error distribution with bounded cumulants. In the case of Gaussian errors, a lower bound on the asymptotic minimax rate in the wavelet coefficient domain is also obtained. Also it is argued that a stronger adaptivity result is possible by the use of a particular location and level dependent threshold obtained by minimizing Stein's unbiased estimate of the risk. In this respect, our work generalizes previous results, which cover the situation of correlated, but stationary errors. A natural application of our approach is the estimation of the trend function of non-stationary time series under the model of local stationarity. The method is illustrated on both an interesting simulated example and a biostatistical data-set, measurements of sheep luteinizing hormone, which exhibits a clear non-stationarity in its variance.     

柏拉图《理想国》中的一个谬误

戴维·萨克斯的这篇发表于1963年的论文是英语世界第一次针对柏拉图<理想国>中的核心论证--正义论证--所做的严格逻辑审查和分析,这篇文章自发表后就产生了广泛的影响,迫使人们以更为严格的方式来面对柏拉图的正义论证,无论是对它进行批判还是为它进行辩护.在这篇论文中,萨克斯敏锐地发现了柏拉图正义论证中的一个所谓不相干的逻辑谬误,即,在最初提出来的是一个关于世俗正义概念的论证要求,但是,在实际的论证过程当中,却被转化为一个关于柏拉图式的正义概念的论证.萨克斯不仅指出了这种概念上的不相干,而且还根据文本进一步分析了是否有可能从柏拉图式的正义概念推导出世俗的正义概念,或者反过来从世俗的正义概念推导出柏拉图式的正义概念,以便有可能为柏拉图的论证做出辩护,但是,作者最终证明,所有这样一些路径在柏拉图那里都是不存在的,从而使得柏拉图式的正义概念和世俗的正义概念之间就存在着根本的逻辑间隙.     

Empowering Rural Sociology: Exploring and Linking Alternative Paradigms in Theory and Methodology1

Abstract Theoretical and methodological approaches to rural social change are explored, especially those that give visibility to the range of heterogeneous experiences and perspectives that often are overlooked or ignored. Theoretical developments in postmodern, narrative, and feminist theory are described as are the methodological approaches they imply. Examples of research on rural social change that attempt to integrate theory and methods in ways that respect the complicated, processual nature of social life are discussed. They provide concrete illustrations of how alternative approaches can be fruitfully applied to some of the issues and problems rural sociologists typically study.