897 resultados para random regression model


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In this study, an attempt is made to assess the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A methodological approach proposed by Dell et al. (2008) is used in preference to the traditional Integrated Assessment Models. The evolution of climate variables and of the macroeconomy of each of the nine countries over the period 1970 to 2006 is analyzed and preliminary evidence of a relationship between the macroeconomy and climate change is examined. The preliminary investigation uses correlation, Granger causality and simple regression methods. The preliminary evidence suggests that there is some relationship but that the direction of causation between the macroeconomy and the climate variables is indeterminate. The main analysis involves the use of a panel data (random effects) model which fits the historical data (1971-2007) very well. Projections of economic growth from 2008 to 2099 are done on the basis of four climate scenarios: the International Panel on Climate Change A2, B2, a hybrid A2B2 (the mid-point of A2 and B2), and a ‘baseline’ or ‘Business as Usual’ scenario, which assumes that the growth rate in the period 2008-2099 is the same as the average growth rate over the period 1971-2007. The best average growth rate is under the B2 scenario, followed by the hybrid A2B2 and A2 scenarios, in that order. Although negative growth rates eventually dominate, they are largely positive for a long time. The projections all display long-run secular decline in growth rates notwithstanding short-run upward trends, including some very sharp ones, moving eventually from declining positive rates to negative ones. The costs associated with the various scenarios are all quite high, rising to as high as a present value (2007 base year) of US$14 billion in 2099 (constant 1990 prices) for the B2 scenario and US$21 billion for the BAU scenario. These costs were calculated on the basis of very conservative estimates of the cost of environmental degradation. Mitigation and adaptation costs are likely to be quite high though a small fraction of projected total investment costs.

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The aim of this study was to estimate genetic parameters for milk yield (MY) in buffaloes using reaction norms. Model included the additive direct effect as random and contemporary group (herd and year of birth) were included as fixed effects and cow age classes (linear) as covariables. The animal additive direct random effect was modeled through linear Legendre polynomials on environment gradient (EG) standardized means. Mean trends were taken into account by a linear regression on Legendre polynomials of environmental group means. Residual variance was modeled trough 6 heterogeneity classes (EG). These classes of residual variance was formed : EG1: mean = 866,93 kg (621,68 kg-1011,76 kg); EG2: mean = 1193,00 kg (1011,76 kg-1251,49 kg); EG3: mean = 1309,37 kg (1251,49 kg -1393,20 kg); EG4: mean = 1497,59 kg (1393,20 kg-1593,53 kg); EG5: mean = 1664,78 kg (1593,53 kg -1727,32kg) e EG6: mean = 1973,85 kg (1727,32 kg -2422,19 kg).(Co) variance functions were estimated by restricted maximum likelihood (REML) using the GIBBS3F90 package. The heritability estimates for MY raised as the environmental gradient increased, varying from 0.20 to 0.40. However, in intermediate to favorable environments, the heritability estimates obtained with Considerable genotype-environment interaction was found for MY using reaction norms. For genetic evaluation of MY is necessary to consider heterogeneity of variances to model the residual variance.

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