Wavelet goodness-of-fit test for dependent data

We introduce a new goodness-of-fit test which can be applied to hypothesis testing about the marginal distribution of dependent data. We derive a new test for the equivalent hypothesis in the space of wavelet coefficients. Such properties of the wavelet transform as orthogonality, localisation and sparsity make the hypothesis testing in wavelet domain easier than in the domain of distribution functions. We propose to test the null hypothesis separately at each wavelet decomposition level to overcome the problem of bi-dimensionality of wavelet indices and to be able to find the frequency where the empirical distribution function differs from the null in case the null hypothesis is rejected. We suggest a test statistic and state its asymptotic distribution under the null and under some of the alternative hypotheses.     

Civil Society Opposition to Nonferrous Metals Mining in Montana

This paper discusses the opposition of civil society to nonferrous metals mining in Montana. The mineral resources and mining history of Montana are discussed, as is the vibrant civil society of that state. Montana’s civil society has opposed mining due to its environmental effects, particularly upon areas of high conservation value. This opposition has involved litigation and the implementation of a ban on the use of cyanide by the mining industry. The paper concludes with a discussion of whether this opposition to mining has damaged the economy of the state and Montana’s future as an example of the “New West,” wherein amenities based growth act as the principal agent of economic activity.     

Exact inference for a simple step-stress model with competing risks for failure from exponential distribution under Type-II censoring

In reliability analysis, accelerated life-testing allows for gradual increment of stress levels on test units during an experiment. In a special class of accelerated life tests known as step-stress tests, the stress levels increase discretely at pre-fixed time points, and this allows the experimenter to obtain information on the parameters of the lifetime distributions more quickly than under normal operating conditions. Moreover, when a test unit fails, there are often more than one fatal cause for the failure, such as mechanical or electrical. In this article, we consider the simple step-stress model under Type-II censoring when the lifetime distributions of the different risk factors are independently exponentially distributed. Under this setup, we derive the maximum likelihood estimators (MLEs) of the unknown mean parameters of the different causes under the assumption of a cumulative exposure model. The exact distributions of the MLEs of the parameters are then derived through the use of conditional moment generating functions. Using these exact distributions as well as the asymptotic distributions and the parametric bootstrap method, we discuss the construction of confidence intervals for the parameters and assess their performance through Monte Carlo simulations. Finally, we illustrate the methods of inference discussed here with an example.     

Anatomie von Kommunikationsrollen

The identification of generalizable roles in social systems has been one of the most central issues in social science ever since. Particularly in the field of interpersonal communication, the notion of communication roles has been used to describe and better understand the complex processes in social groups and society. This contribution identifies the theoretical and methodological concepts that have to be considered when roles in directed networks are operationalized. Based on a network analytic approach and critically evaluating the shortcomings of some widely used models, this study aims to propose new concepts for the operationalization of communication roles. These concepts can be divided into two distinctive approaches. One possibility is to use microstructures like dyadic and triadic communication roles as basic units. For this approach, different aggregation rules are discussed which are necessary for their application in more complex networks. The second approach takes the overall structure of a network into account and identifies different roles by applying centrality measures, blockmodelling or hierarchical structure analysis tools. For illustrative reasons, this study limits its focus on the operationalization of communication roles as a prominent object in social science research. The concepts presented, however, are applicable for directed graphs in general.     

COVARIANCE MODELS FOR LATTICE DATA

Given observations on an m × n lattice, approximate maximum likelihood estimates are derived for a family of models including direct covariance, spatial moving average, conditional autoregressive and simultaneous autoregressive models. The approach involves expressing the (approximate) covariance matrix of the observed variables in terms of a linear combination of neighbour relationship matrices, raised to a power. The structure is such that the eigenvectors of the covariance matrix are independent of the parameters of interest. This result leads to a simple Fisher scoring type algorithm for estimating the parameters. The ideas are illustrated by fitting models to some remotely sensed data.     

How Resource Dependency Can Influence Social Resilience within a Primary Resource Industry*

Abstract Maintaining a healthy balance between human prosperity and environmental integrity is at the core of the principles of Ecological Sustainable Development. Resource‐protection policies are frequently implemented so as to regulate the balance between resource access and use, however, they can inadvertently compromise the ability of resource users to adapt and be resilient. Resource users who are especially dependent on a resource are more seriously compromised. But how do we define and measure resource dependency? And how do we assess its ability to influence social resilience? In this study, a conceptual model of resource dependency is developed in terms of: (i) occupational attachment, (ii) attachment to place, (iii) employability, (iv) family attitude to change, (v) business size, (vi) business approach, (vii) financial situation, (viii) level of specialisation, (ix) time spent harvesting, and (x) interest in and knowledge of the environment. The model of resource dependency and its effect on social resilience are (quantitatively and qualitatively) tested and explored using the commercial fishing industry in North Queensland, Australia. Results show that occupational attachment and employability were important influences as were business size and approach. Results can be used to identify vulnerability to institutional change and guide policy development processes.