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Slash Spatial Linear Modeling: Soybean Yield Variability as a Function of Soil Chemical Properties Rev. Bras. Ciênc. Solo
Fagundes,Regiane Slongo; Uribe-Opazo,Miguel Angel; Guedes,Luciana Pagliosa Carvalho; Galea,Manuel.
ABSTRACT: In geostatistical modeling of soil chemical properties, one or more influential observations in a dataset may impair the construction of interpolation maps and their accuracy. An alternative to avoid the problem would be to use most robust models, based on distributions that have heavier tails. Therefore, this study proposes a spatial linear model based on the slash distribution (SSLM) in order to characterize the spatial variability of soybean yields as a function of soil chemical properties. The likelihood ratio statistic (LR) was applied to verify the significance of parameters associated with the model. We evaluated the sensitivity of the maximum likelihood estimators by means of local influence analysis for both the soybean response and the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Spatial variability; Slash distribution; Maximum likelihood; Yield estimators.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100301
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