Fuzzy K-means clustering models for triangular fuzzy time trajectories

We focus our attention on the classification of fuzzy time trajectories with triangular membership function, described by a given set of individuals. To this purpose, we adopt a fullyinformational approach, explicitly recognizing the informational nature shared by the ingredients of the classification procedure: the observed data (Empirical Information) and the classification model (Theoretical Information). In particular, by supposing that the informational paradigm has a fuzzy nature, we suggest three fuzzy clustering models allowing the classification of the triangular fuzzy time trajectories, based on the analysis of the cross sectional and/or longitudinal characteristics of their components (centers and spreads). Two applicative examples are illustrated.     

Testing Inference in Inflated Beta Regressions under Model Misspecification

We consider testing inference in inflated beta regressions subject to model misspecification. In particular, quasi-z tests based on sandwich covariance matrix estimators are described and their finite sample behavior is investigated via Monte Carlo simulations. The numerical evidence shows that quasi-z testing inference can be considerably more accurate than inference made through the usual z tests, especially when there is model misspecification. Interval estimation is also considered. We also present an empirical application that uses real (not simulated) data.     

Odd-Burr generalized family of distributions with some applications

We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.     

The Decomposition of Economic Outcomes as a Result of Changes in Brazil’s Male Age–Education Structure

In Brazil, the age and education compositions of the male labor force is changing with great regional variation. Based on Demographic Census microdata, results indicate that cohort size has a negative impact on earnings, but this effect is decreasing over time. In this study we consider the impact on earnings by age and education, as well as estimated income inequality reduction and racial differentials. Fertility decline and improve regarding educational attainment had a significant influence on the decline of income inequality in the country. Moreover, the non-white population has been experiencing less success in relation to educational achievement, compared to the white population.     

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.     

Landscape urbanization threatens plant phylogenetic diversity in the Brazilian Atlantic Forest

Urbanization causes species loss around the world, but its effects on phylogenetic diversity are poorly known in tropical forests. Using a patch-landscape approach in an urbanizing region of the Brazilian Atlantic Forest, we tested whether the increase in landscape urbanization reduces plant species density, phylogenetic richness and divergence, and increases the relatedness among co-occurring individuals and species. We assessed plant responses to urbanization in adult (diameter at breast height?>?10 cm) and sapling communities (2.5–10 cm diameter) separately, as saplings are proxies of the future flora. We sampled 2860 woody plants belonging to 155 species in nine circular landscapes with urbanization level varying from 0% to 45%, and estimated the relatedness among the species that have increased and decreased in relative abundance in more urbanized landscapes (winner and losers, respectively). As expected, species density and phylogenetic richness decreased with the increase in urbanization. These responses were consistent for adult and sapling communities, suggesting a persistent loss of species and lineages in more urbanized landscapes. Contrary to our expectations, phylogenetic divergence and structure did not respond to urbanization, indicating that the more urbanized landscapes still retain much evolutionary history. However, because the relatedness among winners was greater than among losers, it is likely that the phylogenetic divergence gradually reduces and the relatedness increases, resulting in impoverished forests with uncertain ability to provide ecosystem services such as carbon storage and pest control. This environmental cost should be taken into account to align urban sprawl with biodiversity conservation.     

Knox meets Cox: Adapting epidemiological space-time statistics to demographic studies

Many important questions and theories in demography focus on changes over time, and on how those changes differ over geographic and social space. Space-time analysis has always been important in studying fertility transitions, for example. However, demographers have seldom used formal statistical methods to describe and analyze time series of maps. One formal method, used widely in epidemiology, criminology, and public health, is Knox’s space-time interaction test. In this article, we discuss the potential of the Knox test in demographic research and note some possible pitfalls. We demonstrate how to use familiar proportional hazards models to adapt the Knox test for demographic applications. These adaptations allow for nonrepeatable events and for the incorporation of structural variables that change in space and time. We apply the modified test to data on the onset of fertility decline in Brazil over 1960–2000 and show how the modified method can produce maps indicating where and when diffusion effects seem strongest, net of covariate effects.     

From “dot.org” to “dot.gov”: Professional Crossings in the Brazilian National Policy on HIV/AIDS

This article reflects on the importance of the relations between state and society in policy-making in the area of public health. Several studies in various sectors such as health, education, and social services have made similar observations on organizational dynamics and the institutionalization of different models of partnerships or contracts, often based on the analytical model of three sectors. Individuals and their networks of relationships, however, remain an almost unexplored dimension in these types of research. Against this backdrop, this study seeks to analyze the movement of HIV/AIDS activists to governmental organizations working in this same field. The analysis raises questions concerning the forms of individual and institutional learning that help to maintain the distinct character of innovation of the Brazilian policy. Professionals who cross the borders hold a different profile once they have accumulated experience working with grassroots and local NGOs, and have also had the chance to be trained and enhance their technical and managerial capacities, since the government has supported NGOs for a long period. When combined, these experiences allow them to maintain relationships with social movements and give them the ability to navigate through the government bureaucracy and handle technical information about fighting AIDS epidemics, making it possible for them to negotiate strategic collaborations reflecting the interests of different groups. Hence, they constantly reflect on the differences between government and social spaces, and keep questioning and modifying their roles in the light of potential and existing complementarities.