A Multiresolution Tree-Structured Spatial Linear Model

2005 ◽  
Vol 14 (1) ◽  
pp. 168-184 ◽  
Author(s):  
Jun Zhu ◽  
Wei Yue
Keyword(s):  
Linear Model ◽  
Spatial Linear Model ◽  
Multiresolution Tree

Influence diagnostics on a reparameterized t-Student spatial linear model

2021 ◽  
Vol 41 ◽  
pp. 100481
Author(s):  
Miguel Angel Uribe-Opazo ◽  
Fernanda De Bastiani ◽  
Manuel Galea ◽  
Rosangela Carline Schemmer ◽  
Rosangela Aparecida Botinha Assumpção
Keyword(s):  
Linear Model ◽  
Influence Diagnostics ◽  
Spatial Linear Model

Robust trend parameters in a multivariate spatial linear model

Test ◽  
2003 ◽  
Vol 12 (2) ◽  
pp. 445-457 ◽  
Author(s):  
Ana F. Militino ◽  
M. Blanca Palacios ◽  
M. Dolores Ugarte
Keyword(s):  
Linear Model ◽  
Spatial Linear Model

scholarly journals Global Influence Diagnostics in Gaussian Spatial Linear Model with Multiple Repetitions

2015 ◽  
Vol 26 ◽  
pp. 74-77 ◽  
Author(s):  
Fernanda De Bastiani ◽  
Miguel A. Uribe-Opazo ◽  
Audrey H. M.A. Cysneiros ◽  
Manuel Galea
Keyword(s):  
Linear Model ◽  
Influence Diagnostics ◽  
Spatial Linear Model ◽  
Global Influence

scholarly journals Comparison of maps of spatial variability of soil resistance to penetration constructed with and without covariables using a spatial linear model

2012 ◽  
Vol 32 (2) ◽  
pp. 393-404 ◽  
Author(s):  
Fernanda de Bastiani ◽  
Miguel A. Uribe-Opazo ◽  
Gustavo H. Dalposso
Keyword(s):  
Spatial Variability ◽  
Linear Model ◽  
Confusion Matrix ◽  
Soil Resistance ◽  
Thematic Maps ◽  
Estimation Model ◽  
The North ◽  
The Matrix ◽  
Spatial Linear Model ◽  
Resistance To Penetration

A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

On multimodality of the likelihood in the spatial linear model

Biometrika ◽  
1989 ◽  
Vol 76 (2) ◽  
pp. 289-295 ◽  
Author(s):  
K. V. MARDIA ◽  
A. J. WATKINS
Keyword(s):  
Linear Model ◽  
Spatial Linear Model

scholarly journals GAUSSIAN SPATIAL LINEAR MODEL OF SOYBEAN YIELD USING BOOTSTRAP METHODS

2018 ◽  
Vol 38 (1) ◽  
pp. 110-116 ◽  
Author(s):  
Gustavo H. Dalposso ◽  
Miguel A. Uribe-Opazo ◽  
Jerry A. Johann ◽  
Manuel Galea ◽  
Fernanda De Bastiani
Keyword(s):  
Linear Model ◽  
Bootstrap Methods ◽  
Soybean Yield ◽  
Spatial Linear Model
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