PGaovR
0.1.1Analysis of Experimental Data using ANOVA and Mean Comparison
Overview
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).
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Health
- OK2026-04-295 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Dependencies
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Code & Tests
- Cyclomatic complexity
- 55.0 median / 68 max
- Documented parameters
- 100%
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
3 3 exported
Complexity
49 avg / 68 max
Call network
3 nodes / 0 edges
Test coverage has not been measured for this package yet; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.1.1Latest
- 0.1.02026-04-29
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-04-29
- Total releases
- 2 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 4.2 KB / 3 files
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet