Perform analysis of variance when the experimental units are spatially correlated. There are two methods to deal with spatial dependence: Spatial autoregressive models (see Scolforo, H.F et al. (2016) <doi:10.1007/s11676-015-0185-y>) 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: | 0.99.0 |
| Depends: | R (≥ 2.10), stats, utils, graphics, geoR, shiny |
| Imports: | MASS, Matrix, ScottKnott, car, gtools, multcomp, multcompView, mvtnorm, devtools, DT, shinyBS, xtable, shinythemes, rmarkdown, knitr, spdep, ape, spatialreg |
| Published: | 2019-07-02 |
| 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 |
| CRAN checks: | spANOVA results |
| Reference manual: | spANOVA.pdf |
| Package source: | spANOVA_0.99.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| OS X binaries: | r-release: not available, r-oldrel: not available |
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