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GAUSSIAN SPATIAL LINEAR MODEL OF SOYBEAN YIELD USING BOOTSTRAP METHODS REA
Dalposso,Gustavo H.; Uribe-Opazo,Miguel A.; Johann,Jerry A.; Galea,Manuel; Bastiani,Fernanda De.
ABSTRACT This study aims to quantify the uncertainties associated to the parameters of a Gaussian spatial linear model (GSLM) and the assumption of normality residuals in the modeling of the spatial dependence of the soybean yield as a function of soil chemical attributes. The spatial bootstrap methods were used to determine the point and interval estimators associated with the model parameters. Hypothesis tests were carried out on the significance of the model parameters and the quantile-quantile probability plot was elaborated to verify the data normality. The uncertainties associated to the parameters of the spatial dependence structure were quantified and the potassium content, phosphorus content and soil pH covariates were significant to explain the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Geostatistics; Spatial resampling; Spatial variability.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100110
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