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 | 
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=spANOVA
to link to this page.