No reliable evidence for immediate noise-induced song flexibility in a suboscine

Urban Ecosystems - Vermilion flycatchers, a suboscine, sing songs with more elements in territories with higher urban noise levels. We tested the hypothesis that this pattern is achieved through...     

Quantifying the synergistic effects of impervious surface and drought on radial tree growth

Urban Ecosystems - The global trend of increasing urbanization is generating isolated patches of vegetation that could be strongly influenced by the surrounding landscape. Simultaneously, many of...     

Large-scale commonness is the best predictor of bird species presence in European cities

Urban Ecosystems - Urban bird communities are homogenized across large spatial scales, suggesting that the urban environment acts as an environmental filter. We hypothesize that large scale...     

Improving citizens’ online engagement via community managers: an explanatory study

The role of community manager is gaining importance as the proper usage of social media becomes a key factor for achieving more active involvement of citizens in social and political issues. Focused on Spanish local governments and in line with the literature of Excellence Theory, this paper aims to analyze whether some characteristics of the community manager function are determinant in their fostering of citizens’ online engagement via social media. In particular ‘independence’, ‘having access to the dominant coalition’, ‘gender diversity’, ‘continuous training’ and ‘culture of the organization’ are the characteristics considered in this paper. As to the main findings, this study confirms that community managers have not as yet achieved their goal of embedding the use of social media by citizens as a means of establishing more direct contact with their local governments. Moreover, in line with Excellence Theory, community managers of local governments should be aware of the importance of having direct access to key managers of the organization in order to better achieve the objectives of the organization and, more specifically, to increase citizens’ engagement. Furthermore, continuous training in issues related to social media truly helps develop the skills and potential of community managers. Likewise, an excellent communication department should rely on good professionals no matter their gender, and, in this sense, the gender of community managers is not a significant factor in their performance. However, the results of this study also reveal that in the case of public sector community managers, an authoritarian culture seems to be a determining factor for obtaining better results in enhancing citizens’ engagement.     

Trend estimation of multivariate time series with controlled smoothness

This paper extends the univariate time series smoothing approach provided by penalized least squares to a multivariate setting, thus allowing for joint estimation of several time series trends. The theoretical results are valid for the general multivariate case, but particular emphasis is placed on the bivariate situation from an applied point of view. The proposal is based on a vector signal-plus-noise representation of the observed data that requires the first two sample moments and specifying only one smoothing constant. A measure of the amount of smoothness of an estimated trend is introduced so that an analyst can set in advance a desired percentage of smoothness to be achieved by the trend estimate. The required smoothing constant is determined by the chosen percentage of smoothness. Closed form expressions for the smoothed estimated vector and its variance-covariance matrix are derived from a straightforward application of generalized least squares, thus providing best linear unbiased estimates for the trends. A detailed algorithm applicable for estimating bivariate time series trends is also presented and justified. The theoretical results are supported by a simulation study and two real applications. One corresponds to Mexican and US macroeconomic data within the context of business cycle analysis, and the other one to environmental data pertaining to a monitored site in Scotland.     

Fourier–type tests involving martingale difference processes

We develop testing procedures which detect if the observed time series is a martingale difference sequence. Furthermore, tests are developed that detect change–points in the conditional expectation of the series given its past. The test statistics are formulated following the approach of Fourier–type conditional expectations first proposed by Bierens (1982 Bierens, H. J. (1982). Consistent model speci?cation tests. J. Econometr. 20:105–134.[Crossref], [Web of Science ®] , [Google Scholar]) and have the advantage of computational simplicity. The limit behavior of the test statistics is investigated under the null hypothesis as well as under alternatives. Since the asymptotic null distribution contains unknown parameters, a bootstrap procedure is proposed in order to actually perform the test. The performance of the bootstrap version of the test is compared in finite samples with other methods for the same problem. A real–data application is also included.     

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.     

<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.     

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.     

Pension reforms in EU11 countries: An evaluation of post‐socialist pension policies

This article evaluates the pension policy pathways of the 11 former state socialist nations that have joined the European Union since 2004. Focusing primarily on the post‐2004 period, the analysis discusses the most important measurable outcomes of these countries’ pension reforms, in terms of poverty alleviation, pension adequacy and fiscal sustainability. Going beyond the quantifiable concepts, we also investigate the quality of the 11 countries’ pension systems in terms of equity as well as efficiency, emphasizing the less conspicuous design errors present in these systems. Although these errors have received little attention to date, they may harm pension schemes along several dimensions, including their fiscal sustainability.