PGaovR: Analysis of Experimental Data using ANOVA and Mean Comparison

Provides tools for designing and analyzing agricultural experiments. It includes functions for generating randomized treatment layouts for standard experimental designs such as Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD), Factorial Randomized Block Design (FRBD), split-plot design, and strip-plot design. The package implements one-factor and two-factor analysis of variance (ANOVA) and offers multiple comparison procedures, including Least Significant Difference (LSD), Tukey, and Duncan tests, to compare treatment means in single-factor and factorial experiments. The methods follow classical experimental design principles described in Gomez and Gomez (1984, Statistical Procedures for Agricultural Research, John Wiley & Sons, New York).

Version: 0.1.0
Depends: R (≥ 3.5)
Imports: ggplot2, grid, multcompView, stats, utils
Published: 2026-04-28
DOI: 10.32614/CRAN.package.PGaovR
Author: Santosh Patil ORCID iD [aut, cre], Yogesh Garde ORCID iD [aut]
Maintainer: Santosh Patil <patil.sgstat at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: PGaovR results

Documentation:

Reference manual: PGaovR.html , PGaovR.pdf

Downloads:

Package source: PGaovR_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: PGaovR_0.1.0.zip, r-oldrel: PGaovR_0.1.0.zip
macOS binaries: r-release (arm64): PGaovR_0.1.0.tgz, r-oldrel (arm64): PGaovR_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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