Package: PGaovR 0.1.1

Santosh Patil

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).

Authors:Santosh Patil [aut, cre], Yogesh Garde [aut]

PGaovR_0.1.1.tar.gz
PGaovR_0.1.1.tar.gz(r-4.7-any)PGaovR_0.1.1.tar.gz(r-4.6-any)
PGaovR_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PGaovR/json (API)

# Install 'PGaovR' in R:
install.packages('PGaovR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 283 downloads 3 exports 18 dependencies

Last updated from:cff7528e00. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK117
source / vignettesOK155
linux-release-x86_64OK127
wasm-releaseOK103

Exports:aov_ofaov_tffld_layout

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclemultcompViewR6RColorBrewerrlangS7scalesvctrsviridisLitewithr