Directional tests and statistical frames

Conditional inference has an ease of implementation that is generally unavailable with marginal inference. The main patterns for conditional inference are provided by the location and transformation families as initiated by Fisher, and by the exponential patterns as initiated by Neyman and Pearson; these are surveyed briefly together with some discussion as to how and why conditioning should be used in inference for them. A more recent alternative pattern is provided by directional (or conical) tests and confidence methods; these lead to conditional inference for simple hypotheses with vector parameters, and can be extended to provide tests for treatment, for variance, and for treatment improvement, in the multivariate analysis of variance context.     

Digital Age Discoverability: A Collaborative Organizational Approach

Abstract

The tumultuous changes in the scholarly communications ecosystem have disrupted traditional library assumptions and established new workflows and user expectations. In response, the Auraria Library at the University of Colorado Denver initiated a collaborative design (co-design) initiative to re-invent structures, processes, services, and roles throughout the entire organization. Fostered by appreciative inquiry, enabled by social learning, and furthered by shared leadership, redesign initiated sustainable information exchange, reflective dialog, and knowledge creation practices.

The case study highlights accomplishments of technical services staff members who successfully engaged co-workers in selection, implementation, and enhancement of a Web-scale discovery service. Continuing support of the full discovery layer lifecycle illustrates evolving information practices and workplace outcomes at the Auraria Library. Concluding reflections offer transferable insights to other organizations aspiring to co-design workplace environments that enliven creativity, discovery, and exploration.     

Higher order local unbiasedness with computer algebra

Unbiased estimation methods that are in some way local on the parameter space have been initiated by Barankin (1948) and Fraser (1964). The later methods involving local unbiasedness are extended to higher (derivative or difference) order at a parameter value (θ) and provide a basis for a computer algebra implementation concerning the improvement of unbiased estimates.     

A strong law of large number for negatively dependent and non identical distributed random variables in the framework of sublinear expectation

Abstract

In this article, in the framework of sublinear expectation initiated by Peng, we derive a strong law of large numbers (SLLN) for negatively dependent and non identical distributed random variables. This result includes and extends some existing results. Furthermore, we give two examples of our result for applications.     

A Paradox on Compartmental Models with Poisson Immigration

Even to the initiated, statistical calculations based on Bayes's Theorem can be daunting because of the numerical integrations required in all but the simplest applications. Moreover, from a teaching perspective, introductions to Bayesian statistics—if they are given at all—are circumscribed by these apparent calculational difficulties. Here we offer a straightforward sampling-resampling perspective on Bayesian inference, which has both pedagogic appeal and suggests easily implemented calculation strategies.     

Using quantile plots of the prediction variance for comparing designs for a constrained mixture region: an application involving a fertilizer experiment

Summary. Vining and co-workers have used plots of the prediction variance trace (PVT) along the so-called prediction rays to compare mixture designs in a constrained region R . In the present paper, we propose a method for describing the distribution of the prediction variance within the region R by using quantile plots. More comprehensive comparisons between mixture designs are possible through the proposed plots than with the PVT plots. The utility of the quantile plots is illustrated with a four-component fertilizer experiment that was initiated in São Paulo, Brazil.     

A strong law of large numbers for independent random variables under non-additive probabilities

Abstract

Under non‐additive probabilities, cluster points of the empirical average have been proved to quasi-surely fall into the interval constructed by either the lower and upper expectations or the lower and upper Choquet expectations. In this paper, based on the initiated notion of independence, we obtain a different Marcinkiewicz-Zygmund type strong law of large numbers. Then the Kolmogorov type strong law of large numbers can be derived from it directly, stating that the closed interval between the lower and upper expectations is the smallest one that covers cluster points of the empirical average quasi-surely.     

Surgical audit: statistical lessons from Nightingale and Codman

There is a long history of interest in examining and comparing surgical outcomes. The 'epidemiological' approach was initiated by Florence Nightingale in her suggestion for uniform surgical statistics, and she clearly predicted the problems that are associated with collecting, analysing and interpreting such data. Unfortunately those responsible for implementing and reporting her scheme appeared not to have shared her insight. The contrasting 'clinical' approach was championed by Ernest Codman in his search for full and honest appraisals of surgical errors. Once again, despite initial enthusiasm, others had great difficulty in following his example, although we discuss a recent instance of a reflective analysis of an individual surgeon's performance. We conclude by suggesting that a synthesis between these approaches is appropriate, but we follow others in warning of the inevitable extra-statistical difficulties that will arise.     

A note on ‘curable’ shock processes

In most conventional shock models, the events caused by an external shock are initiated at the moments of its occurrence. Recently, Cha and Finkelstein (2012) had considered the case when each shock from a nonhomogeneous Poisson processes can trigger a failure of a system not immediately, as in the classical shock models, but with delay of some random time. In this paper, we suggest the new type of shock models, where each delayed failure can be cured (repaired) with certain probabilities. These shock processes have not been considered in the literature before. We derive and analyze the corresponding survival and failure rate functions and consider a meaningful reliability example of the stress–strength model.     

A stochastic process approach to multilayer neutron detectors

The sparsity of the isotope Helium‐3, ongoing since 2009, has initiated a new generation of neutron detectors. One particularly promising development line for detectors is the multilayer gaseous detector. In this paper, a stochastic process approach is used to determine the neutron energy from the additional data afforded by the multilayer nature of these novel detectors. The data from a multilayer detector consist of counts of the number of absorbed neutrons along the sequence of the detector's layers, in which the neutron absorption probability is unknown. We study the maximum likelihood estimator for the intensity and absorption probability and show its consistency and asymptotic normality, as the number of incoming neutrons goes to infinity. We combine these results with known results on the relation between the absorption probability and the wavelength to derive an estimator of the wavelength and to show its consistency and asymptotic normality.     

Mixture inverse Gaussian for unobserved heterogeneity in the autoregressive conditional duration model

In this paper, we assume that the duration of a process has two different intrinsic components or phases which are independent. The first is the time it takes for a trade to be initiated in the market (for example, the time during which agents obtain knowledge about the market in which they are operating and accumulate information, which is coherent with Brownian motion) and the second is the subsequent time required for the trade to develop into a complete duration. Of course, if the first time is zero then the trade is initiated immediately and no initial knowledge is required. If we assume a specific compound Bernoulli distribution for the first time and an inverse Gaussian distribution for the second, the resulting convolution model has a mixture of an inverse Gaussian distribution with its reciprocal, which allows us to specify and test the unobserved heterogeneity in the autoregressive conditional duration (ACD) model.

Our proposals make it possible not only to capture various density shapes of the durations but also easily to accommodate the behaviour of the tail of the distribution and the non monotonic hazard function. The proposed model is easy to fit and characterizes the behaviour of the conditional durations reasonably well in terms of statistical criteria based on point and density forecasts.     

Single-Stop Ebook Reader “SimplyE”: Is It APPlicable for Academic Libraries?

Accessing ebooks from different vendors often requires switching between multiple platforms, which can be unwieldy for library users. To offer readers a coherent and seamless reading experience, the New York Public Library (NYPL) initiated a project called SimplyE (or LibrarySimplified). The end user deliverable of this project is an application (Android, iOS) that enables users to read ebooks from multiple vendors through a single interface, thereby delivering a Netflix-style experience for searching, browsing, and checking out ebooks. The back end consists of applications that manage ebook collections, circulation, and metadata for libraries. This column explores the viability of implementing SimplyE in an academic library setting.     

A Gaussian alternative to using improper confidence intervals

The problem posed by exact confidence intervals (CIs) which can be either all-inclusive or empty for a nonnegligible set of sample points is known to have no solution within CI theory. Confidence belts causing improper CIs can be modified by using margins of error from the renewed theory of errors initiated by J. W. Tukey—briefly described in the article—for which an extended Fraser's frequency interpretation is given. This approach is consistent with Kolmogorov's axiomatization of probability, in which a probability and an error measure obey the same axioms, although the connotation of the two words is different. An algorithm capable of producing a margin of error for any parameter derived from the five parameters of the bivariate normal distribution is provided. Margins of error correcting Fieller's CIs for a ratio of means are obtained, as are margins of error replacing Jolicoeur's CIs for the slope of the major axis. Margins of error using Dempster's conditioning that can correct optimal, but improper, CIs for the noncentrality parameter of a noncentral chi-square distribution are also given.     

A Bayesian criterion for selecting super saturated screening designs

Super-saturated designs in which the number of factors under investigation exceeds the number of experimental runs have been suggested for screening experiments initiated to identify important factors for future study. Most of the designs suggested in the literature are based on natural but ad hoc criteria. The “average s²” criteria introduced by Booth and Cox (Technometrics 4 (1962) 489) is a popular choice. Here, a decision theoretic approach is pursued leading to an optimality criterion based on misclassification probabilities in a Bayesian model. In certain cases, designs optimal under the average s² criterion are also optimal for the new criterion. Necessary conditions for this to occur are presented. In addition, the new criterion often provides a strict preference between designs tied under the average s² criterion, which is advantageous in numerical search as it reduces the number of local minima.     

Enhancement of the adaptive signature design for learning and confirming in a single pivotal trial

Because of the complexity of cancer biology, often the target pathway is not well understood at the time that phase III trials are initiated. A 2‐stage trial design was previously proposed for identifying a subgroup of interest in a learn stage, on the basis of 1 or more baseline biomarkers, and then subsequently confirming it in a confirmation stage. In this article, we discuss some practical aspects of this type of design and describe an enhancement to this approach that can be built into the study randomization to increase the robustness of the evaluation. Furthermore, we show via simulation studies how the proportion of patients allocated to the learn stage versus the confirm stage impacts the power and provide recommendations.     

中国住房市场政府干预的原理与效果评价

 本文首先在住房存量流量模型的基础上,对住房市场政府干预的政策目标和政策工具进行了理论刻画,然后联合应用干预分析模型和面板数据模型就2003年以来住房市场政府干预的主要政策组合对北京、上海、广州、深圳、天津和重庆6重点城市的作用效果进行了定量评价。结果表明：全国性政策工具对重点城市住房价格产生了显著的长短期干预效果,尤其是2005年和2006年国务院的两次综合干预以不同形式和力度抑制了房价增长;政府干预的有效性逐渐提升,但全国性政策工具对不同城市的作用力度有显著差异,表现为对二线城市房价的抑制作用明显高于一线城市;2004年土地交易制度改革可能是造成近年住房价格上升的主要政策因素之一。     

SPC—a team effort for process improvement across four Area Control Centres

This paper describes an innovative application of statistical process control to the online remote control of the UK's gas transportation networks. The gas industry went through a number of changes in ownership, regulation, access to networks, organization and management culture in the 1990s. The application of SPC was motivated by these changes along with the desire to apply the best industrial statistics theory to practical problems. The work was initiated by a studentship, with the technology gradually being transferred to the industry. The combined efforts of control engineers and statisticians helped develop a novel SPC system. Having set up the control limits, a system was devised to automatically update and publish the control charts on a daily basis. The charts and an associated discussion forum are available to both managers and control engineers throughout the country at their desktop PCs. The paper describes methods of involving people to design first-class systems to achieve continual process improvement. It describes how the traditional benefits of SPC can be realized in a 'distal team working', and 'soft systems', context of four Area Control Centres, controlling a system delivering two thirds of the UK's energy needs.