986 resultados para Estimated parameters
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Mechanical operations such as mowing, tilling, seeding, and harvesting are well-known sources of direct avian mortality in agricultural fields. However, there are currently no mortality rate estimates available for any species group or larger jurisdiction. Even reviews of sources of mortality in birds have failed to address mechanical disturbance in farm fields. To overcome this information gap we provide estimates of total mortality rates by mechanical operations for five selected species across Canada. In our step-by-step modeling approach we (i) quantified the amount of various types of agricultural land in each Bird Conservation Region (BCR) in Canada, (ii) estimated population densities by region and agricultural habitat type for each selected species, (iii) estimated the average timing of mechanical agricultural activities, egg laying, and fledging, (iv) and used these values and additional demographical parameters to derive estimates of total mortality by species within each BCR. Based on our calculations the total annual estimated incidental take of young ranged from ~138,000 for Horned Lark (Eremophila alpestris) to as much as ~941,000 for Savannah Sparrow (Passerculus sandwichensis). Net losses to the fall flight of birds, i.e., those birds that would have fledged successfully in the absence of mechanical disturbance, were, for example ~321,000 for Bobolink (Dolichonyx oryzivorus) and ~483,000 for Savannah Sparrow. Although our estimates are subject to an unknown degree of uncertainty, this assessment is a very important first step because it provides a broad estimate of incidental take for a set of species that may be particularly vulnerable to mechanical operations and a starting point for future refinements of model parameters if and when they become available.
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Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h(2)) was 0.012 to 0.028 and of permanent environmental variance (c(2)) was 0.016 to 0.032. Genetic correlations (r(g)) among fertility traits were generally high ( > 0.70). Genetic correlations of fertility with milk production traits were unfavourable (range -0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h(2) and c(2) were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69-0.83 for all animals in the pedigree and 0.89-0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended. (C) 2002 Elsevier Science B.V. All rights reserved.
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The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported. (C) 2011 Elsevier B.V. All rights reserved.
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Diffusion coefficients and retardation factors of two metal cations (Cd2+ and Pb2+) were measured for a compacted Brazilian saprolitic soil derived from gneiss, aiming to assess its geoenvironmental performance as a liner for waste disposal sites. This soil occurs extensively all over the country in very thick layers, but has not been used in liners because of its hydraulic conductivity, higher than 10(-9) m/s when compacted at optimum water content of standard Proctor energy, but which can be reduced by means of appropriate compaction techniques or additives. Batch, column, and diffusion tests were carried out with monospecies synthetic solutions at pH 1, 3, and 5.5. Measured diffusion coefficients varied between 0.5 and 4 X 10(-10) m(2)/s. Retardation factors show that cadmium, a very mobile cation, is not adsorbed at pH I but is significantly retained at pH 3 and pH 5.5, whereas lead is retained at all tested pH values though slightly at pH 1. Estimated retardation factors from batch tests were 1.3-2.3 times those resulting from column tests and at its highest when obtained by diffusion tests; whereas batch tests allow a more complete exposure of the soil grains to the solution, time-dependent nonspecific adsorption may take longer to occur. The importance of contact time was observed and should be considered in further investigations. Its significant retention of metals suggests a promising utilization of this soil as a bottom liner for wastes landfills.
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Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.
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When estimating policy parameters, also known as treatment effects, the assignment to treatment mechanism almost always causes endogeneity and thus bias many of these policy parameters estimates. Additionally, heterogeneity in program impacts is more likely to be the norm than the exception for most social programs. In situations where these issues are present, the Marginal Treatment Effect (MTE) parameter estimation makes use of an instrument to avoid assignment bias and simultaneously to account for heterogeneous effects throughout individuals. Although this parameter is point identified in the literature, the assumptions required for identification may be strong. Given that, we use weaker assumptions in order to partially identify the MTE, i.e. to stablish a methodology for MTE bounds estimation, implementing it computationally and showing results from Monte Carlo simulations. The partial identification we perfom requires the MTE to be a monotone function over the propensity score, which is a reasonable assumption on several economics' examples, and the simulation results shows it is possible to get informative even in restricted cases where point identification is lost. Additionally, in situations where estimated bounds are not informative and the traditional point identification is lost, we suggest a more generic method to point estimate MTE using the Moore-Penrose Pseudo-Invese Matrix, achieving better results than traditional methods.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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(Co) variance components were estimated for visual scores of conformation (CY), early finishing (PY) and muscling (MY) at 550 days of age (yearling), average daily gain from weaning to yearling (GWY), conformation (CW), early finishing (PW) and muscling (MW) scores at weaning, and average daily gain from birth to weaning (GBW) in animals forming the Brazilian Brangus breed born between 1986 and 2002 from the livestock files of GenSys Consultants Associados S/C Ltda. The data set contained 53 683; 45 136; 52 937; 56 471; 24 531; 21 166; 24 006 and 25 419 records for CW, PW, MW, GBW, CY, PY, MY and GWY, respectively. Data were analyzed by the restricted maximum likelihood method using single-and two-trait animal models. Direct heritability estimates obtained by single-trait analysis were 0.12, 0.14, 0.13 and 0.14 for CY, PY and MY scores and GWY, respectively. A positive association was observed between the same visual scores at weaning and yearling, with correlations ranging from 0.64 to 0.94. Estimated correlations between GBW and weaning and yearling scores ranged from 0.60 to 0.77. The genetic correlation between GBW and GWY was low (0.10), whereas correlations of 0.55, 0.37 and 0.47 were observed between GWY and CY, PY and MY, respectively. Moreover, GWY showed a weak correlation with CW (0.10), PW (-0.08) and MW (-0.03) scores. These results indicate that selection of the traits that was studied would result in a small response. In addition, selection based on average daily gain may have an indirect effect on visual scores as the correlations between GWY and visual scores were generally strong.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Estimaram-se fatores de correção para produção de leite aos 90, 240, 270 e 305 dias de lactação e parâmetros genéticos e de ambiente da produção de leite ajustada para esses períodos de lactação, utilizando-se 3888 lactações de 1630 búfalas, controladas entre 1987 e 2001, em 10 rebanhos do Estado de São Paulo. Os parâmetros genéticos foram estimados por meio do método da máxima verossimilhança restrita, livre de derivadas, aplicado a um modelo animal com medidas repetidas. As estimativas de herdabilidade para produção de leite corrigida para 90, 240, 270 e 305 dias de lactação foram 0,17; 0,15; 0,14 e 0,14, respectivamente. Nessa mesma ordem de apresentação, as estimativas de repetibilidade foram 0,40; 0,44; 0,41 e 0,41. As estimativas de correlação genética entre essas produções de leite corrigidas variaram de 0,96 a 1,00. Os fatores de correção multiplicativos para as diferentes classes de duração da lactação foram eficientes para ajustar a produção de leite aos 90, 240, 270 e 305 dias de lactação.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)