Beyond the average: Detecting global singular nodes from local features in complex networks

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barabasi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks. Copyright (C) EPLA, 2009

Average Annual Wind Resource Potential in Maine

http://digitalcommons.colby.edu/atlasofmaine2006/1000/thumbnail.jpg

Educational Opportunities and Average Income in Maine Towns

http://digitalcommons.colby.edu/atlasofmaine2006/1015/thumbnail.jpg

Average Annual Precipitation in Maine

http://digitalcommons.colby.edu/atlasofmaine2005/1011/thumbnail.jpg

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

The distribution of average and marginal effective tax rates in European Union member states

Macro-based summary indicators of effective tax burdens do not capture differences in effective tax rates facing different sub-groups of the population. They also cannot provide information on the level or distribution of the marginal effective tax rates thought to influence household behaviour. I use EUROMOD, an EU-wide tax-benefit microsimulation model, to compute distributions of average and marginal effective tax rates across the household population in fourteen European Union Member States. Using different definitions of ‘net taxes’, the tax base and the unit of analysis I present a range of measures showing the contribution of the tax-benefit system to household incomes, the average effective tax rates applicable to income from labour and marginal effective tax rates faced by working men and women. In a second step, effective tax rates are broken down to separately show the influence of each type of tax-benefit instrument. The results show that measures of effective tax rates vary considerably depending on incomes, labour market situations and family circumstances. Using single averages or macro-based indicators will therefore provide an inappropriate picture of tax burdens faced by large parts of the population.

Evaluation of an average numerator relationship matrix model and a Bayesian hierarchical model for growth traits in Nellore cattle with uncertain paternity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Study of relations among age at first calving, average weight gains and weights from weaning to maturity in Nellore cattle

Dados de 23.120 animais da raça Nelore foram utilizados para estimar herdabilidade e correlações genéticas para a idade ao primeiro parto, o ganho em peso da desmama ao ano e do ano ao sobreano, o peso à desmama, o peso ao ano, o peso ao sobreano e os pesos aos 2 e aos 5 anos de idade. Utilizou-se o método da máxima verossimilhança restrita, em análise multicaracterística. As herdabilidades estimadas para idade ao primeiro parto, ganho da desmama ao ano, ganho do ano ao sobreano, peso à desmama, peso ao ano, peso ao sobreano e peso aos 2 aos 5 anos foram de 0,17 ± 0,01; 0,23 ± 0,03; 0,25 ± 0,03; 0,28 ± 0,02; 0,26 ± 0,03; 0,30 ± 0,03; 0,32 ± 0,02 e 0,36 ± 0,04, respectivamente. Correlações genéticas baixas e negativas foram estimadas entre a idade ao primeiro parto e os pesos medidos em diferentes idades, que variaram de -0,26 a -0,14. As correlações genéticas estimadas entre a idade ao primeiro parto e os ganhos de peso também foram negativas, porém levemente superiores (-0,29 e -0,32). Os resultados indicam que a seleção para maior ganho de peso pode reduzir a idade ao primeiro parto e aumentar o peso adulto de fêmeas da raça Nelore. Mudança genética mais rápida para diminuição da idade ao primeiro parto das fêmeas pode ser obtida com a inclusão dessa característica nos índices de seleção.

Modeling of average growth curve in Santa Ines sheep using random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Prediction of intake and average daily gain by different feeding systems for goats

A main purpose of a mathematical nutrition model (a.k.a., feeding systems) is to provide a mathematical approach for determining the amount and composition of the diet necessary for a certain level of animal productive performance. Therefore, feeding systems should be able to predict voluntary feed intake and to partition nutrients into different productive functions and performances. In the last decades, several feeding systems for goats have been developed. The objective of this paper is to compare and evaluate the main goat feeding systems (AFRC, CSIRO, NRC, and SRNS), using data of individual growing goat kids from seven studies conducted in Brazil. The feeding systems were evaluated by regressing the residuals (observed minus predicted) on the predicted values centered on their means. The comparisons showed that these systems differ in their approach for estimating dry matter intake (DMI) and energy requirements for growing goats. The AFRC system was the most accurate for predicting DMI (mean bias = 91 g/d, P < 0.001; linear bias 0.874). The average ADG accounted for a large part of the bias in the prediction of DMI by CSIRO, NRC, and, mainly, AFRC systems. The CSIRO model gave the most accurate predictions of ADG when observed DMI was used as input in the models (mean bias 12 g/d, P < 0.001; linear bias -0.229). while the AFRC was the most accurate when predicted DMI was used (mean bias 8g/d. P > 0.1; linear bias -0.347). (C) 2011 Elsevier B.V. All rights reserved.

Double sampling (x)over-bar control chart for a first-order autoregressive moving average process model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Acoustic and perceptual analyses of Brazilian male actors' and nonactors' voices: Long-term average spectrum and the Actor's Formant

This study investigates the possible differences between actors' and nonactors' vocal projection strategies using acoustic and perceptual analyses. A total of 11 male actors and 10 male nonactors volunteered as subjects, reading an extended text sample in habitual, moderate, and loud levels. The samples were analyzed for sound pressure level (SPL), alpha ratio (difference between the average SPL of the 1-5 kHz region and the average SPL of the 50 Hz-1 kHz region), fundamental frequency (F0), and long-term average spectrum (LTAS). Through LTAS, the mean frequency of the first formant (171) range, the mean frequency of the actor's formant, the level differences between the F1 frequency region and the F0 region (L1-L0), and the level differences between the strongest peak at 0-1 kHz and that at 3-4 kHz were measured. Eight voice specialists evaluated perceptually the degree of projection, loudness, and tension in the samples. The actors had a greater alpha ratio, stronger level of the actor's formant range, and a higher degree of perceived projection and loudness in all loudness levels. SPL, however, did not differ significantly between the actors and nonactors, and no differences were found in the mean formant frequencies ranges. The alpha ratio and the relative level of the actor's formant range seemed to be related to the degree of perceived loudness. From the physiological point of view, a more favorable glottal setting' providing a higher glottal closing speed, may be characteristic of these actors' projected voices. So, the projected voices, in this group of actors, were more related to the glottic source than to the resonance of the vocal tract.

Effect of boron and zinc fertilization on white oats grown in soil with average content of these nutrients

The objective of this study was to evaluate the effect of fertilization with zinc or boron on the growth and dry matter production, nutritional value and accumulation of nutrients in white oats. The study comprised two experiments conducted in glasshouses, the first consisting of the application of four doses of zinc (0, 0.2, 0.4 and 0.6 mg/dm³) in the form of zinc sulphate (20% Zn), and the second consisting of the application of four doses of boron (0, 0.2, 0.4 and 0.6 mg/dm³) in the form of Borax (11% B). The experimental design in each case was a randomized block design, with five replicates. Fertilization with zinc and boron increased the growth of white oats, but had no significant effect on the nutritional value of the forage. Higher levels of absorption and accumulation of nutrients in plant tissues were observed following the application of boron and zinc at rates of up to 0.60 mg/dm³ of soil.