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: 0.99.1
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: 2019-08-21
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

Downloads:

Reference manual: spANOVA.pdf
Package source: spANOVA_0.99.1.tar.gz
Windows binaries: r-devel: spANOVA_0.99.1.zip, r-release: spANOVA_0.99.1.zip, r-oldrel: spANOVA_0.99.1.zip
OS X binaries: r-release: spANOVA_0.99.1.tgz, r-oldrel: spANOVA_0.99.1.tgz
Old sources: spANOVA archive

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