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aridagri  

Comprehensive Statistical Tools for Agricultural Research
View on CRAN: Click here


Download and install aridagri package within the R console
Install from CRAN:
install.packages("aridagri")

Install from Github:
library("remotes")
install_github("cran/aridagri")

Install by package version:
library("remotes")
install_version("aridagri", "2.0.4")



Attach the package and use:
library("aridagri")
Maintained by
Lalit Kumar Rolaniya
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-24
Latest Update: 2026-02-24
Description:
A comprehensive suite of statistical and analytical tools for agricultural research. Includes complete analysis of variance (ANOVA) functions for all experimental designs: Completely Randomized Design (CRD), Randomized Block Design (RBD), Pooled RBD, Split Plot with all variations, Split-Split Plot, Strip Plot, Latin Square, Factorial, Augmented, and Alpha Lattice, with proper error terms and comprehensive Standard Error (SE) and Critical Difference (CD) calculations. Features multiple post-hoc tests: Least Significant Difference (LSD), Duncan Multiple Range Test (DMRT), Tukey Honestly Significant Difference (HSD), Student-Newman-Keuls (SNK), Scheffe, Bonferroni, and Dunnett, along with assumption checking and publication-ready output. Advanced methods include stability analysis using Eberhart-Russell regression, Additive Main Effects and Multiplicative Interaction (AMMI), Finlay-Wilkinson regression, Shukla stability variance, Wricke ecovalence, Coefficient of Variation (CV), and Cultivar Superiority Index as described in Eberhart and Russell (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>. Thermal indices include Growing Degree Days (GDD), Heliothermal Units (HTU), Photothermal Units (PTU), and Heat Use Efficiency (HUE). Crop growth analysis covers Crop Growth Rate (CGR), Relative Growth Rate (RGR), Net Assimilation Rate (NAR), and Leaf Area Index (LAI). Also provides harvest index, yield gap analysis, economic efficiency indices (Benefit-Cost ratio), nutrient use efficiency calculations, correlation matrix, Principal Component Analysis (PCA), path analysis, and Structural Equation Modeling (SEM). Statistical methods follow Gomez and Gomez (1984, ISBN:0471870927) and Panse and Sukhatme (1985, ISBN:8170271169).
How to cite:
Lalit Kumar Rolaniya (2026). aridagri: Comprehensive Statistical Tools for Agricultural Research. R package version 2.0.4, https://cran.r-project.org/web/packages/aridagri. Accessed 13 Oct. 2026.
Previous versions and publish date:
(2026-07-10 20:00), 2.0.3 (2026-02-24 20:20)
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Complete documentation for aridagri
Functions, R codes and Examples using the aridagri R package
Full aridagri package functions and examples
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