981 resultados para geoestatística multivariada
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The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The soybean crop is considered a high expression around the world. In plant breeding programs, knowledge of genetic diversity is extremely important and in this context, are frequently used multivariate analyzes. Thus, the aim of the present study was to evaluate the genetic divergence between soybean crosses through multivariate techniques. In total, 16 crosses were evaluated, which were in the F2 generation of inbreeding. The evaluated characteristics were plant height at maturity, height of the first pod, number of branches per plant, number of pods per plant, number of nodes per plant, hundred seed weight, grain yield and oil content. For the analyzes was used Euclidean distance, methods of hierarchical clustering UPGMA and Ward and principal component analysis. Genetic distances estimated using Euclidean distance ranged from 1.24 to 8.13, with the smallest distance observed between crosses C1 and C4, and the greatest distance between the C2 crosses and C6. The methods UPGMA clustering and Ward met crossings in five different groups. The principal component analysis explained 86.2% of the variance contained in the original eight variables with three main components. The APM characters, NV, NR, NN, PG% and oil were the main contributors to genetic divergence among traits. Multivariate techniques were crucial to the analysis of genetic diversity, and the methods of Ward and UPGMA clustering and principal components have consistent results in this way, the simultaneous use of these tools in genetic analysis of crosses is indicated
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Classical statistical techniques which necessarily assume that all sampling units are random and independent were always used in the timber industry. Geostatistics considers that certain phenomena are characterized by spatial dependence: values of sampling units closer to each other tend to be more similar than values of sampling units farther away. This study aimed to characterize the spatial variability of the finishing (dyer) in the upper and lower surfaces of four edge glued panels by using geostatistical methods using geoR. Semivariograms were constructed for the analysis of spatial dependence. The spherical mathematical model was the best fit to the semivariograms generated, and was done the interpolation of the data (kriging) in samples where the distribution of dyer presents spatial dependence. In the bottom surfaces of two panels where the spatial dependence was detected geostatistical methods characterized a very large spatial variability due to the heterogeneous application of the finishing
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A análise estatística multivariada, extensão da análise univariada, consiste num conjunto de técnicas estatísticas, aplicadas quando há diversas variáveis relacionadas simultaneamente, sendo todas elas, em princípio, consideradas importantes no fenômeno em estudo. É de grande aplicação a conjuntos de dados das mais diversas áreas do conhecimento, principalmente da área biológica. Seu desenvolvimento teve um grande impulso na primeira metade do século passado. Entretanto, devido a complexidade dos cálculos matemáticos, principalmente envolvendo operações com matrizes de altas ordens, as aplicações somente se popularizaram nos dias atuais, com o desenvolvimento dos computadores e aplicativos computacionais. Técnicas estudadas: distâncias multivariadas, componentes principais, análise fatorial, correlações canônicas, análise de correspondência, teste t² de Hotelling, análise de variância multivariada (Manova), teste de normalidade multivariada, igualdade de matrizes de variâncias e covariâncias para populações multinormais
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Pós-graduação em Medicina Veterinária - FCAV
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV
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Pós-graduação em Engenharia de Produção - FEB
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The objective of this paper is to relate the set of financial ratios that are directly related to the success of public traded companies using a methodological approach and the method of multivariate principal component analysis. This study consists in the use of profitability ratios, debt and liquidity, to define the relationship between financial ratios with the best public traded companies listed in the magazine Exame Melhores e Maiores of 2013. Multivariate analysis was used to reduce the dimensionality of multivariate data, making linear combinations of the original variables (financial ratios) and express the data in principal components that result in new variables that contains much of the original data. As a result, we got the optimal number of five principal components, and both represent 95.6% of the original data. Among of all financial ratios, we can highlight the direct relationship between profitability ratios for the first principal component, and the direct relationship between the liquidity ratios, both inversely related with non-capital participation rates and degree indebtedness to the second principal component
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Pós-graduação em Agronomia (Entomologia Agrícola) - FCAV
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The purpose of this paper was to evaluate the influence of different implant designs on the micromovements of immediately placed implants. CT-based finite element models comprising an upper central incisor socket and four commercially available internal connection implant designs (SIN SW®, 3i Certain®, Nobel ReplaceTM, and RN synOcta® ITI Standard) of comparable diameter and length were constructed. 50, 100 and 200N magnitude loads were applied over the implant. ANOVA at 95% level of significance was used to evaluate bone to implant relative displacement (micromovements). The implant design (68,80%) greatly influences the micromovement of immediately placed implants. However, the loading magnitude (68,80%) is the most important factor regarding the implant stability in this protocol.
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Pós-graduação em Química - IQ
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Pós-graduação em Química - IQ