The Overlooked Potential of Generalized Linear Models in Astronomy-III: Bayesian Negative Binomial Regression and Globular Cluster Populations

In this paper, the third in a series illustrating the power of generalized linear models (GLMs) for the astronomical community, we elucidate the potential of the class of GLMs which handles count data. The size of a galaxy's globular cluster population $N_{\rm GC}$ is a prolonged puzzle in the astronomical literature. It falls in the category of count data analysis, yet it is usually modelled as if it were a continuous response variable. We have developed a Bayesian negative binomial regression model to study the connection between $N_{\rm GC}$ and the following galaxy properties: central black hole mass, dynamical bulge mass, bulge velocity dispersion, and absolute visual magnitude. The methodology introduced herein naturally accounts for heteroscedasticity, intrinsic scatter, errors in measurements in both axes (either discrete or continuous), and allows modelling the population of globular clusters on their natural scale as a non-negative integer variable. Prediction intervals of 99% around the trend for expected $N_{\rm GC}$comfortably envelope the data, notably including the Milky Way, which has hitherto been considered a problematic outlier. Finally, we demonstrate how random intercept models can incorporate information of each particular galaxy morphological type. Bayesian variable selection methodology allows for automatically identifying galaxy types with different productions of GCs, suggesting that on average S0 galaxies have a GC population 35% smaller than other types with similar brightness.Comment: 14 pages, 12 figures. Accepted for publication in MNRA

Components of multifractality in the Central England Temperature anomaly series

We study the multifractal nature of the Central England Temperature (CET) anomaly, a time series that spans more than 200 years. The series is analyzed as a complete data set and considering a sliding window of 11 years. In both cases, we quantify the broadness of the multifractal spectrum as well as its components defined by the deviations from the Gaussian distribution and the influence of the dependence between measurements. The results show that the chief contribution to the multifractal structure comes from the dynamical dependencies, mainly the weak ones, followed by a residual contribution of the deviations from Gaussianity. However, using the sliding window, we verify that the spikes in the non-Gaussian contribution occur at very close dates associated with climate changes determined in previous works by component analysis methods. Moreover, the strong non-Gaussian contribution found in the multifractal measures from the 1960s onwards is in agreement with global results very recently proposed in the literature.Comment: 21 pages, 10 figure

Evaluation of Tropical and Subtropical Forage Grasses in the Northwest Region of Rio Grande Do Sul, Brazil

A collection of 137 accessions of tropical and subtropical grasses of Pennisetum purpureum (53), Panicum maximum (10), Brachiaria spp. (9), Hemarthria altissima (19), Setaria spp. (11), Digitaria spp. (22), Cynodon spp.(7) and Paspalum spp. (6) was evaluated for frost tolerance (FT), dry matter yield per cut (DMYC), number of cuts (NC) and accumulated dry matter yield per year (ADMY). Crude protein content (CPC), leaf/stem ratio (L/S), pubescence (P) and animal preference under grazing (AP) were also recorded in 20 entries of in P. purpureum. Data exploration involved cluster analysis and ordination, revealing the most promising entries among and within genus. In general ADMY and FT were the most important variables to discriminate entries. Pennisetum, Panicum and Hemarthria were the most productive genus with high FT. Cynodon and Paspalum showed high FT

The Overlooked Potential of Generalized Linear Models in Astronomy - I: Binomial Regression

Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought. Contemporary data analysis problems often elude the capabilities of classical statistical techniques, suggesting the use of cutting edge statistical methods. In this light, astronomers have overlooked a whole family of statistical techniques for exploratory data analysis and robust regression, the so-called Generalized Linear Models (GLMs). In this paper -- the first in a series aimed at illustrating the power of these methods in astronomical applications -- we elucidate the potential of a particular class of GLMs for handling binary/binomial data, the so-called logit and probit regression techniques, from both a maximum likelihood and a Bayesian perspective. As a case in point, we present the use of these GLMs to explore the conditions of star formation activity and metal enrichment in primordial minihaloes from cosmological hydro-simulations including detailed chemistry, gas physics, and stellar feedback. We predict that for a dark mini-halo with metallicity $\approx 1.3 \times 10^{-4} Z_{\bigodot}$, an increase of $1.2 \times 10^{-2}$ in the gas molecular fraction, increases the probability of star formation occurrence by a factor of 75%. Finally, we highlight the use of receiver operating characteristic curves as a diagnostic for binary classifiers, and ultimately we use these to demonstrate the competitive predictive performance of GLMs against the popular technique of artificial neural networks.Comment: 20 pages, 10 figures, 3 tables, accepted for publication in Astronomy and Computin

Disponibilidade de água no Latossolo Amarelo Distrocoeso em função da aplicação de diferentes doses de carvão.

A caracterização de condicionadores de solo é fator crucial para a sua recomendação e uso. As análises da Terra Preta Arqueológica (TPA) revelaram particularidades de grande interesse agrícola, o que tem sido útil para o desenvolvimento de materiais fertilizantes mais eficientes.Em paralelo aconteceram também os seguintes eventos: V Seminário de Pesquisa do Recôncavo da Bahia; V Seminário Estudantil de Pesquisa da UFRB; V Seminário da Pós-Graduação da UFRB; II Seminário Regional de Pesquisa da EBDA; 5ª Jornada Científica da Embrapa Mandioca e Fruticultura; VIII Seminário Estudantil de Pesquisa e Extensão da FAMAM; Semana de Ciência, Tecnologia e Inovação no Agronegócio; Fórum de Gestores de Iniciação Científica e Tecnológica da Bahia; II Simpósio Baiano de Defesa Agropecuária; I Semana de Educação Tutorial da UFRB

Uso da alelopatia como alternativa de controle de plantas infestantes em citros.

A citricultura brasileira apresenta números expressivos que traduzem a grande importância econômica e social que a atividade tem para a economia do país. Nessa direção, este trabalho estuda alternativas de manejo e controle de plantas infestantes para a cultura dos citros, visando sua sustentabilidade e redução dos custos com insumos, sobretudo herbicidas, em pomares localizados nos solos dos Tabuleiros Costeiros, a partir da supressão da interferência da matovegetação pela ação alelopática de palhadas de coberturas vegetais (roçadas), tanto nativas como implantadas, avaliando sua eficiência e comportamento como auxiliares no controle do mato.PDF. 193_11