A new estimation method for Weibull-type tails based on the mean excess function

Studying the right tail of a distribution, one can classify the distributions into three classes based on the extreme value index γ$\gamma$. The class γ>0$\gamma >0$ corresponds to Pareto-type or heavy tailed distributions, while γ<0$\gamma <0$ indicates that the underlying distribution has a finite endpoint. The Weibull-type distributions form an important subgroup within the Gumbel class with γ=0$\gamma =0$. The tail behaviour can then be specified using the Weibull tail index. Classical estimators of this index show severe bias. In this paper we present a new estimation approach based on the mean excess function, which exhibits improved bias and mean squared error. The asserted properties are supported by simulation experiments and asymptotic results. Illustrations with real life data sets are provided.     

Revisiting the model of creative destruction: St. Jacobs,Ontario, a decade later

Ten years ago, the model of creative destruction was developed to predict the fate of communities that base their development on the commodification of rural heritage (Mitchell, C.J.A., 1998. Entrepreneurialism, commodification and creative destruction: a model of post-modern community development. Journal of Rural Studies 14, 273–286). Its application to the village of St. Jacobs, Canada, demonstrated that entrepreneurial investment had fostered the creation of a setting for aestheticized consumption. In this paper we demonstrate that creative destruction has continued to unfold in the village over the course of the past decade. The evolutionary path taken is assessed in light of current literature on rural space. It is concluded that to fully understand the transformative process, one must integrate the demands of myriad sub-cultures, whose social relations, ideologies and actions will contribute to the development of a contested landscape of consumption. This finding necessitates that modifications be made to the model and its various stages. The most significant is recognition that the “heritage-scape” is an interim state of landscape change; one that displaces the productivist landscape of the industrial period, and precedes the creation of the “neo-productivist” leisure-scape of post-industrialism. Whether or not such a “final” state is achieved is dictated by the power struggle that inevitably arises amongst sub-cultures engaged in the transformation of rural space.     

An emplrical bayes approach in estimating the parameters of the or more geometric distributions

The estimation of the parameters of two or more geometric distribuionsis considered by usinq an empirical Bayesian approach. Robbins (1983) gave empirical Bayes estimates if the number of distributions N is large, buthere we consider the cascwhore N is small. The parameters of the prior distribution areest imated by looking at maximum like lihood and momentest imation methods.     

A procedure to select a ML-II prior in a multivariate normal case

Berger (1985) derived a procedure to select a maximum likelihood II prior distribution. In this paper a method is suggested to construct such a prior distribution from a multivariate ε-contamination class of distributions. The method is illustrated by the conetruction of a ML-II prior in the multivariate normal case.     

Understanding the philosophical positions of classical and neopragmatists for mixed methods research

Pragmatism is the most popular philosophy/paradigm in the international field of mixed methods research (MMR). This article therefore introduces, describes, and contrasts the philosophies of the most well known pragmatists, including the three most important classical pragmatists (Charles Sanders Peirce, William James and John Dewey) and two neopragmatists (Richard Rorty and Susan Haack). It is shown that Rorty and James fit well with qualitatively driven MMR (i.?e., MMR where the qualitative component of the study is primary); Peirce fits well with quantitatively driven MMR (i.?e., MMR where the quantitative component is primary); and Dewey fits well with MMR that attempts to treat qualitative and quantitative research/philosophy equally (i.?e., equal-status mixed methods research). Importantly, it is shown here that pragmatism offers a way out of many philosophy of science quagmires facing social researchers and it offers a promising philosophy for mixed methods research practice.     

Why are Depressive Symptoms More Prevalent Among The Less Educated? The Relevance of Low Cultural Capital and Cultural Entitlement

Analyzing nationally representative survey data collected in the United States in 2014 (n?=?1,932), we formulate and test a novel explanation for the educational gradient in depressive symptoms. We theorize that status as cultural capital drives this gradient in addition to well-established economic and social factors, via the feelings of cultural entitlement it inspires. Therefore, we use structural equation modeling to decompose the education effect. We demonstrate that in addition to economic (job security and income) and social factors (embeddedness in the neighborhood), cultural capital indeed accounts for the educational gradient in depressive symptoms via cultural entitlement. We conclude that for understanding social gradients in mental health it is vital to be sensitive for the cultural mechanisms that status as cultural capital can inspire. Based on our findings we propose suggestions for further research.     

Occupancy distributions for testing marginal homogeneity

In this paper different pairs of urns are considered. We are interested in the number of ways in which N balls can be placed into the urns so that differences and ratios between the number of balls in certain pairs of urns are the same.     

The use of utilities and experts in decision-making

In the process of decision-making the decision-maker may be able to consult an expert or experts or there may be no experts available. Four different situations that the decision-maker may be confronted with, are considered. The utilities of the decision-maker are used in this decision-making process to obtain his Bayes decision. The four different situations are illustrated by an example.