Data/hora: 13/06/2024 04:20:04

Provedor de dados: | 118
País: | Chile
Título: | Local influence when fitting Gaussian spatial linear models: an agriculture application
Autores: | Grzegozewski,Denise M; Uribe-Opaz,Miguel A; De Bastiani,Fernanda; Galea,Manuel.
Data: | 2013-12-01
Ano: | 2013
Palavras-chave: | Geostatistical; Influence diagnostics; Maximum likelihood; Outliers; Spatial variability.
Resumo: | D.M. Grzegozewski, M.A. Uribe-Opazo, F. De Bastiani, and M. Galea. 2013. Local influence when fitting Gaussian spatial linear models: an agriculture application. Cien. Inv. Agr. 40(3): 523-535. Outliers can adversely affect how data fit into a model. Obviously, an analysis of dependent data is different from that of independent data. In the latter, i.e., in cases involving spatial data, local outliers can differ from the data in the neighborhood. In this article, we used the local influence technique to identify influential points in the response variables using two different schemes of perturbations. We applied this technique to soil chemical properties and soybean yield. We evaluated the effects of the influential points on the spatial model selection, the parameter estimation by maximum likelihood and the construction of thematic maps by kriging. In the construction of the thematic maps in studies with and without the influential points, there were changes in the levels of nutrients, allowing for the appropriate application of input, generating greater savings for the producer and contributing to the protection of the environment.
Tipo: | Journal article
Idioma: | Inglês
Identificador: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202013000300006
Editor: | Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal
Formato: | text/html
Fonte: | Ciencia e investigación agraria  v.40 n.3 2013