Detalhes bibliográficos
| Ano de defesa: |
2012 |
| Autor(a) principal: |
Grzegozewski, Denise Maria
 |
| Orientador(a): |
Opazo, Miguel Angel Uribe
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Estadual do Oeste do Parana
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação "Stricto Sensu" em Engenharia Agrícola
|
| Departamento: |
Engenharia
|
| País: |
BR
|
| Palavras-chave em Português: |
|
| Palavras-chave em Inglês: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tede.unioeste.br:8080/tede/handle/tede/2878
|
Resumo: |
Soy is one of the main crops in Brazil and in the region of Cascavel / PR, where agricultural production is large, although some factors that affect productivity, monitoring and process management have been diagnosed by geostatistical models for analysis of agricultural data. Studies on the spatial variability of soil attributes associated with soybean yield, provide recommendations for doses o with varied rates, according to the maps created by spatial models. The diagnostic study on influential points is a recommended procedure for studies on spatial variability. Detecting the influential points through local influence allows measuring the changes that these points have influence on and the construction of the thematic map. This paper aims to present studies on local influence in linear spatial models considering as dependent variable soybean yield and as covariates Carbon (C), Calcium (Ca), Potassium (K), Magnesium (Mg), Manganese (Mn) and Phosphorus (P). The study on local influence is held in the response variable and the covariates using additive disturbances. The techniques of local influence diagnostics, according to the final results, were efficient in identifying outliers considered influential variables for the individual linear spatial model |
