Analysis of Field Trials with Geostatistics & Spatial AR Models R package spANOVA version 0.99.4 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. Software 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 Castro L. R. <lucasroberto.castro@gmail.com> Comprehensive R Archive Network (CRAN) Castro L. R. [aut, cre, cph], Renato R. R. [aut, ths], Rossoni D. F. [aut], Nogueira C.H. [aut] GPL-3 2024-03-21 application/tgz https://CRAN.R-project.org/package=spANOVA doi:10.32614/CRAN.package.spANOVA