spANOVA: Analysis of Field Trials with Geostatistics & Spatial AR Models
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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