Simulation for the complex Bingham distribution

The complex Bingham distribution is relevant for the shape analysis of landmark data in two dimensions. In this paper it is shown that the problem of simulating from this distribution reduces to simulation from a truncated multivariate exponential distribution. Several simulation methods are described and their efficiencies are compared.     

Aboriginal Harvesting in the Moose River Basin: A Historical and Contemporary Analysis

Les territoires traditionnels de chasse et de trappe des Cris dans les régions méridionales du bassin de Moose River ont été infiltrés au début du XXe siècle, par les colons euro-canadiens et l'exploitation des ressources qui s'est ensuivie, avec l'encouragement actif du gouvernement provincial. Après la Deuxième Guerre mondiale, ces tendances se sont également propagées au nord du bassin. Selon de nombreux contemporains, l'économie basée sur la chasse et la trappe des Cris s'était désintégrée face à la concurrence des Euro-Canadiens et l'appât du travail rémunéré et de la vie villageoise. Cependant, de récentes études sur le terrain démontrent l'importance continue et la viabilité de l'économie autochtone traditionnelle du bassin de Moose River.
The traditional hunting and trapping territories of the Cree in the southern reaches of the Moose River Basin were infiltrated by Euro-Canadian settlement and resource-based development early in the 20th century, with the active encouragement of the provincial government. After the Second World War, these trends were also evident in the northern part of the Basin. Many contemporaries believed that the Cree hunting and trapping economy had disintegrated in the face of Euro-Canadian competition and the lure of wage labour and village life. However, recent field studies document the continuing importance and viability of the traditional aboriginal economy of the Moose River Basin.     

The Effectiveness of Environmental Civil Society Organizations: An Integrated Analysis of Organizational Characteristics and Contextual Factors

A push to reverse unsustainable trends has come from environmental civil society, but its track record is somewhat inconsistent. Why are some environmental organizations able to enhance the environmental cause, while others fail to create a substantial impact in the move toward environmental sustainability? This paper considers related but disparate clusters of literature and identifies factors that have an impact on the effectiveness of civil society. It also addresses the ambiguity that is attached to civil society—a concept with considerable historical baggage and contextual differentiation. Given that each conceptualization of civil society has its own body of literature and that these do not necessarily speak to each other, we propose an analytical framework that integrates a variety of dimensions relevant to the analysis of environmental civil society organizations (CSOs): the degree of institutionalization, the mode of interaction with the state, sources of funding, the locus of mobilization, the choice of issue(s), and the degree of politicization. Using these organizational characteristics, our framework further integrates contextual factors, constructing a multidimensional space where there are opportunities and constraints for environmental CSOs. This framework allows us to examine diverse paths shaped by context-dependent strategic choices of environmental CSOs which may either limit or enhance their capacity to make an impact. These strategic choices are tracked by selecting entry points inspired by fieldwork conducted in Turkey—specifically, institutionalization, the choice of issue(s), and politicization.     

Evaluating the Significance Test When the Correlation Coefficient is Different from Zero in the Test of Hypothesis

Sample size and correlation coefficient of populations are the most important factors which influence the statistical significance of the sample correlation coefficient. It is observed that for evaluating the hypothesis when the observed value of the correlation coefficient's r is different from zero, Fisher's Z transformation may be incorrect for small samples especially when population correlation coefficient ρ has big values. In this study, a simulation program has been generated for to illustrate how the bias in the Fisher transformation of the correlation coefficient affects estimate precision when sample size is small and ρ has big value. By the simulation results, 90 and 95% confidence intervals of correlation coefficients have been created and tabled. As a result, it is suggested that especially when ρ is greater than 0.2 and sample sizes of 18 or less, Tables 1 and 2 can be used for the significance test in correlations.     

Reinstituting the Economic Process: (Re)embedding the Economy in Society and Nature

Polanyi argued that the project of creating a fully self-regulating market was utopian, in the sense of impossible. However, movement towards this utopia, the ever greater but never completed process of disembedding the economy from both society and nature, creates growing dislocations and tensions which call forth a counter movement. This double movement may be thought of as successive changes in the way in which the economic process is instituted. The focus of the paper is on the meaning of embeddedness, the ways in which the economy was reinstituted during the Great Transformation and the subsequent counter movements, and alternative approaches to further reinstituting the economy in ways that disembed it further or (re)embed it more firmly in society and nature. It is argued that prior to the creation of the capitalist market the economy was organically embedded in society and nature. However, the creation of separate economic institutions, the institution of the economic process as a distinct system with its own laws of motion, severed these organic links and the economy came to dominate both society and nature. Here, however, the symmetry between society and nature ends. Society has the capacity for conscious, purposeful action; nature does not. For the economy to be reinstituted in ways that create a sustainable organic relationship with nature, it must first be reinstituted in ways that bring it under social control.     

Detecting changes in the mean of functional observations

Summary.  Principal component analysis has become a fundamental tool of functional data analysis. It represents the functional data as X _i ( t )= μ ( t )+Σ_{1≤ l <∞} η _{i ,  l} +  v _l ( t ), where μ is the common mean, v _l are the eigenfunctions of the covariance operator and the η _{i ,  l} are the scores. Inferential procedures assume that the mean function μ ( t ) is the same for all values of i . If, in fact, the observations do not come from one population, but rather their mean changes at some point(s), the results of principal component analysis are confounded by the change(s). It is therefore important to develop a methodology to test the assumption of a common functional mean. We develop such a test using quantities which can be readily computed in the R package fda. The null distribution of the test statistic is asymptotically pivotal with a well-known asymptotic distribution. The asymptotic test has excellent finite sample performance. Its application is illustrated on temperature data from England.     

Testing for changes in the covariance structure of linear processes

We consider several procedures to detect changes in the mean or the covariance structure of a linear process. The tests are based on the weighted CUSUM process. The limit distributions of the test statistics are derived under the no change null hypothesis. We develop new strong and weak approximations for the sample mean as well as the sample correlations of linear processes. A small Monte Carlo simulation illustrates the applicability of our results.