spANOVA: Analysis of Field Trials with Geostatistics & Spatial AR Models (original) (raw)
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: | 0.99.4 |
|---|---|
| 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: | 2024-03-21 |
| DOI: | 10.32614/CRAN.package.spANOVA |
| Author: | Castro L. R. [aut, cre, cph], Renato R. R. [aut, ths], Rossoni D. F. [aut], Nogueira C.H. [aut] |
| Maintainer: | Castro L. R. <lucasroberto.castro at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | spANOVA results |
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