spANOVA: Spatial Analysis of Field Trials Experiments using Geostatistics
and Spatial Autoregressive Model
Perform analysis of variance when the experimental units are spatially correlated. There are two methods to deal with spatial dependence: Spatial autoregressive models (see Rossoni, D. F., & Lima, R. R. (2019) <doi:10.28951/rbb.v37i2.388>) and geostatistics (see Pontes, J. M., & Oliveira, M. S. D. (2004) <doi:10.1590/S1413-70542004000100018>). For both methods, there are three multicomparison procedure available: Tukey, multivariate T, and Scott-Knott.
| Version: |
0.99.3 |
| Depends: |
R (≥ 2.10), stats, utils, graphics, geoR, shiny |
| Imports: |
MASS, Matrix, ScottKnott, car, gtools, multcomp, multcompView, mvtnorm, DT, shinyBS, xtable, shinythemes, rmarkdown, knitr, spdep, ape, spatialreg, shinycssloaders |
| Published: |
2021-06-11 |
| Author: |
Lucas Roberto de Castro, Renato Ribeiro de Lima, Diogo Francisco Rossoni, Cristina Henriques Nogueira |
| Maintainer: |
Lucas Roberto de Castro <lrcastro at estudante.ufla.br> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
spANOVA results |
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