The exponential distribution analog of the Grubbs–Weaver method

Abstract

Grubbs and Weaver (1947 Grubbs, F. E., and C. L. Weaver. 1947. The best unbiased estimate of population standard deviation based on group ranges. Journal of the American Statistical Association 42 (238):224–41. doi: 10.2307/2280652.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) suggest a minimum-variance unbiased estimator for the population standard deviation of a normal random variable, where a random sample is drawn and a weighted sum of the ranges of subsamples is calculated. The optimal choice involves using as many subsamples of size eight as possible. They verified their results numerically for samples of size up to 100, and conjectured that their “rule of eights” is valid for all sample sizes. Here we examine the analogous problem where the underlying distribution is exponential and find that a “rule of fours” yields optimality and prove the result rigorously.     

Language skills and homophilous hiring discrimination: Evidence from gender and racially differentiated applications

Review of Economics of the Household - This paper investigates the importance of ethnic homophily in the hiring discrimination process. Our evidence comes from a correspondence test performed in...     

Coalitions of Actors and Managerial Innovations in the Healthcare and Social Healthcare Sector

This paper studies the behavior of a variety of stakeholders around the adoption of managerial innovations desired by operational managers of health services institutions. We show that if the operational manager may cause the managerial innovation, the tool prospective is subject to power games around coalitions of actors. The study of several management situations in health services institutions enables us, using the game theory, to highlight the “winning”, “losing” and “uncertain” coalitions that can achieve operational management within the establishment to settle a managerial innovation.     

Simultaneous model-based clustering and visualization in the Fisher discriminative subspace

Clustering in high-dimensional spaces is nowadays a recurrent problem in many scientific domains but remains a difficult task from both the clustering accuracy and the result understanding points of view. This paper presents a discriminative latent mixture (DLM) model which fits the data in a latent orthonormal discriminative subspace with an intrinsic dimension lower than the dimension of the original space. By constraining model parameters within and between groups, a family of 12 parsimonious DLM models is exhibited which allows to fit onto various situations. An estimation algorithm, called the Fisher-EM algorithm, is also proposed for estimating both the mixture parameters and the discriminative subspace. Experiments on simulated and real datasets highlight the good performance of the proposed approach as compared to existing clustering methods while providing a useful representation of the clustered data. The method is as well applied to the clustering of mass spectrometry data.     

Quand la formation ne suffit pas : la préparation des étudiants à l’emploi en Angleterre,en France et en Suède

The proliferation of internships and the rise of professionalisation in higher education are, in France, frequently condemned as evidence of a quest for greater employability, driven by a skills-based approach. A comparative analysis of the methods used to prepare students for employment shows the degree to which the social mechanisms are homogeneous in England (employability) and in Sweden (bildning). In France, the transition from higher education to employment entails a process of pre-professionalisation. This is characterised by the dominant role of professional skills and their incorporation into the structure of initial education itself. Rather than the outcome of a process of commodification, this mechanism of pre-professionalisation is explained by the persistence of an idealized conception of “matching” that still profoundly marks the relations between education and employment in France.     

Restructuring of the Financial Industry: The Disappearance of Locally Owned Traditional Financial Services in Rural America

Restructuring in the financial services industry has altered the relationship between small business owners and capital. In the past small businesses have relied on relational, or soft data, lending from locally owned banks for capital. The proliferation of absentee‐owned local branch networks brought standardized practices, thus eliminating the autonomy of local loan officers to utilize soft data in loan decisions. In this article we examine the changes in the percentage of traditional financial services that are locally owned in three county types: metropolitan, micropolitan, and noncore. We utilize the Longitudinal Business Database at the U.S. Census Bureau Center for Economic Studies. We examine changes in local ownership of traditional financial services between 1976 and 2007. We find that the rate of decline of local ownership has been greatest in the noncore (most rural) counties. We also explore to what extent these patterns are related to the emergence of alternative financial services during the same period. We find that such alternative services are growing in all three county types, but at rates not significantly different than the population growth for these county types. We supplement our analysis with data from qualitative interviews with small business owners throughout rural Texas. We conclude with a discussion of implications and plans for future research.