Bayesian analysis of elapsed times in continuous‐time Markov chains

The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software.     

Optimal representative sample weighting

Statistics and Computing - To overcome the inherent limitations of axis-aligned base learners in ensemble learning, several methods of rotating the feature space have been discussed in the...     

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.     

A Multidimensional Approach to Precarious Employment Among Young Workers in EU-28 Countries

This article uses a new multidimensional indicator to measure precariousness among young workers across all EU-28 countries. This indicator measures both the incidence and intensity of precariousness. The analysis has involved five dimensions: wages, type of contract, type of working day, disempowerment, and job insecurity. Our database is the European Union Labour Force Survey for the period 2009–2016. The main indication of precariousness is low wages. We find high rates of precariousness for Mediterranean countries (because of low wages and temporary contracts), Denmark (low wages), and the Netherlands (expansion of involuntary part-time jobs). Central European countries have moderate rates, and most Continental and Eastern countries have low rates. We also find that a higher level of education is related to a lower probability of having a precarious job. Finally, we find a greater probability of having a precarious job among women in most countries, and non-statistically significant differences by country of birth.

     

Intensive management reduces butterfly diversity over time in urban green spaces

Urban Ecosystems - Loss and fragmentation of semi-natural grasslands have had negative consequences for grassland biodiversity, such as butterflies. Urban parks and other urban green spaces have so...     

Multivariate log-Birnbaum–Saunders regression models

In this paper, we present a multivariate version of the skewed log-Birnbaum–Saunders regression model. This new family of distributions holds good properties such as marginal variables following univariate skewed log-Birnbaum–Saunders distributions, besides presenting the usual log-Birnbaum–Saunders distribution as a particular case. Furthermore, the model parameters are estimated through maximum-likelihood methods, a closed-form expression for the Fisher’s information matrix is presented, and testing hypothesis for model parameters is performed. Two real datasets are analyzed and results are discussed.     

Fast parallel $$\alpha $$-stable distribution function evaluation and parameter estimation using OpenCL in GPGPUs

\(\alpha \)-Stable distributions are a family of probability distributions found to be suitable to model many complex processes and phenomena in several research fields, such as medicine, physics, finance and networking, among others. However, the lack of closed expressions makes their evaluation analytically intractable, and alternative approaches are computationally expensive. Existing numerical programs are not fast enough for certain applications and do not make use of the parallel power of general purpose graphic processing units. In this paper, we develop novel parallel algorithms for the probability density function and cumulative distribution function—including a parallel Gauss–Kronrod quadrature—, quantile function, random number generator and maximum likelihood estimation of \(\alpha \)-stable distributions using OpenCL, achieving significant speedups and precision in all cases. Thanks to the use of OpenCL, we also evaluate the results of our library with different GPU architectures.     

Influence of urbanization on the occurrence and activity of aerial insectivorous bats

Activity and species-specific responses of insectivorous bats in different urban-forest conditions provides a general perspective on the adaptability and vulnerability of bat species towards urbanization intensity. Here we evaluated species richness and activity patterns of aerial insectivorous bats across an urbanized landscape in the highlands of Chiapas, in Mexico. Acoustic monitoring of echolocation calls was conducted for 27 nights over a period of four months. Species richness and relative activity of insectivorous bats were estimated in a landscape with different conditions of urbanization intensity: urban areas, non-urban and forest areas. We identified a total of 14 bat species and three phonotypes. Bat species richness and relative activity was similar (X² = 0.568, gl = 2, p > 0.05), but species composition differed among conditions. We observed a significant higher occurrence of Bauerus dubiaquercus, Eptesicus brasiliensis and Myotis californicus in forest sites. Urban sites presented higher occurrence of Molossus rufus and phonotype Molossidae 2, while non-urban sites presented a higher occurrence of Eptesicus furinalis and phonotype Molossidae 2. We were able to identify bat species according to their relative activity in relation todifferent landscape conditions. Species of the Molossidae family presented the highest activity in urban sites, which was positively affected by the number of streetlights, while species of the Vespertilionidae presented the highest activity in forest sites, which was positively related totree density. While urbanization tends to diminish native biodiversity and alter faunal communities, our results show a similar richness and relative activity of aerial insectivorous bats along the urban ecosystem. The effect of urbanization intensity becomes more apparent in species-specific bat activity; the response of species towards particular habitat conditions depends on local habitat quality and characteristics (i.e., presence of streetlights, vegetation cover and tree density).