Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.     

Public intellectuals,political satire and the birth of activist public relations: The case of Attic Comedy

The purpose of this article is to explore the origins of dissent public relations and to establish its emergence in the context of the ancient Greek comedy represented by Aristophanes. Indeed, Attic Comedy (also known as Old Comedy) was the first great example of today’s mass communication, in which political satire was used to dissent and protest against political and social circumstances in fifth-century BC Athens. This situation was conditioned by the Peloponnesian War and its political, economic and social consequences. From this perspective, this article also constitutes an investigation into the intellectual history of public relations, of which Aristophanes can be considered to be one of the first practitioners.     

Job-Related Well-Being of Immigrants

Social Indicators Research - Considerable literature exists on the acculturation and adaptation of immigrants. For the most part, studies looked at their psychological and social adaptation to the...     

Activity patterns and temporal niche partitioning of dogs and medium-sized wild mammals in urban parks of Xalapa,Mexico

Urban Ecosystems - Free-ranging domestic dogs are the world most common exotic carnivore species that could negatively interact with the native wildlife as predators, competitors, and disease...     

Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

Seasonal fractional ARIMA (ARFISMA) model with infinite variance innovations is used in the analysis of seasonal long-memory time series with large fluctuations (heavy-tailed distributions). Two methods, which are the empirical characteristic function (ECF) procedure developed by Knight and Yu [The empirical characteristic function in time series estimation. Econometric Theory. 2002;18:691–721] and the Two-Step method (TSM) are proposed to estimate the parameters of stable ARFISMA model. The ECF method estimates simultaneously all the parameters, while the TSM considers in the first step the Markov Chains Monte Carlo–Whittle approach introduced by Ndongo et al. [Estimation of long-memory parameters for seasonal fractional ARIMA with stable innovations. Stat Methodol. 2010;7:141–151], combined with the maximum likelihood estimation method developed by Alvarez and Olivares [Méthodes d'estimation pour des lois stables avec des applications en finance. Journal de la Société Française de Statistique. 2005;1(4):23–54] in the second step. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques.     

COWORDS: a probabilistic model for multiple word clouds

Word clouds constitute one of the most popular statistical tools for the visual analysis of text documents because they provide users with a quick and intuitive understanding of the content. Despite their popularity for visualizing single documents, word clouds are not appropriate to compare different text documents. Independently generating word clouds for each document leads to configurations where the same word is typically located in widely different positions. This makes it very difficult to compare two or more word clouds. This paper introduces COWORDS, a new stochastic algorithm to create multiple word clouds, including one for each document. The shared words in multiple documents are placed in the same position in all clouds. Similar documents produce similar and compact clouds, making it easier to simultaneously compare and interpret several word clouds. The algorithm is based on a probability distribution in which the most probable configurations are those with a desirable visual aspect, such as a low value for the total distance between the words in all clouds. The algorithm output is a set of word clouds that are randomly selected from this probability distribution. The selection procedure uses a Markov chain Monte Carlo simulation method. We present several examples that illustrate the performance and visual results that can be obtained by our algorithm.     

Corporate social responsibility and governance

Journal of Management and Governance -     

Is there a global super-bourgeoisie?

In recent decades, accelerating processes of globalization and an increase in economic inequality in most of the world's countries have raised the question of the emergence of a new bourgeoisie integrated at the global level, sometimes described as a global super-bourgeoisie. This group would be distinguished by its unequaled level of wealth and global interconnectedness, its transnational ubiquity and concentration in the planet's major global cities, its specific culture, consumption habits, sites of sociability and shared references, and even by class consciousness and capacity to act collectively. This article successively discusses how the social sciences have examined these various dimensions of the question and begun to provide systematic empirical answers.     

Models of the Joint Structure of Domain-Related and Global Distress: Implications for the Reconciliation of Quality of Life and Mental Health Perspectives

Research on subjective wellbeing includes studies of both domain-related and global distress. The mental health literature, though, focuses almost exclusively on global distress. This seems to be partly due to a common belief that psychological distress, and the moods that comprise distress, necessarily lack referential content. However, if that were the case it would make little sense for any study to ever focus on domain-related distress. The research presented in this report clarifies the relation between global and domain-related distress. We compare confirmatory factor analytic models of the joint relationship among symptoms of global distress with affective symptoms of distress about work, home, and physical appearance. Data are from a general population telephone survey. In the best-fitting models domain-related distress and global psychological distress are related but distinct latent variables. We discuss the theoretical and methodological implications of the models, and model choice.