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AgroR

Package: AgroR

Type: Package

Title: Experimental Statistics and Graphics for Agricultural Sciences

Version: 1.3.6

Date: 2023-26-12

Authors:

  • Gabriel Danilo Shimizu
  • Rodrigo Yudi Palhaci Marubayashi
  • Leandro Simoes Azeredo Goncalves

Maintainer: Gabriel Danilo Shimizu shimizu@uel.br

Description: Performs the analysis of completely randomized experimental designs (CRD), randomized blocks (RBD) and Latin square (LSD), experiments in double and triple factorial scheme (in CRD and RBD), experiments in subdivided plot scheme (in CRD and RBD), subdivided and joint analysis of experiments in CRD and RBD, linear regression analysis, test for two samples. The package performs analysis of variance, ANOVA assumptions and multiple comparison test of means or regression, according to Pimentel-Gomes (2009, ISBN: 978-85-7133-055-9), nonparametric test (Conover, 1999, ISBN: 0471160687), test for two samples, joint analysis of experiments according to Ferreira (2018, ISBN: 978-85-7269-566-4) and generalized linear model (glm) for binomial and Poisson family in CRD and RBD (Carvalho, FJ (2019), <doi: 10.14393/ufu.te.2019.1244>). It can also be used to obtain descriptive measures and graphics, in addition to correlations and creative graphics used in agricultural sciences (Agronomy, Zootechnics, Food Science and related areas).

Encoding: UTF-8

RoxygenNote: 7.1.1

Imports: ggplot2, nortest, lme4, crayon, lmtest, emmeans, multcomp, ggrepel, MASS, cowplot, multcompView, RColorBrewer, drc, dunn.test, gtools

Suggests: DT, knitr, rmarkdown, roxygen2

Depends: R (>= 3.6.0)

License: GPL (>= 2)

Installation

# Install release version from CRAN
install.packages("AgroR")

# Install development version from GitHub
devtools::install_github("https://github.com/AgronomiaR/AgroR.git")

References

Data set

  • aristolochia: Germination of seeds of Aristolochia sp. as a function of temperature.
  • bean: Bean data
  • cloro: Sodium dichloroisocyanurate in soybean
  • corn: Corn data
  • covercrops: Covercrops data
  • emerg: Emergence of passion fruit seeds over time .
  • enxofre: Sulfur data
  • laranja: Orange plants under different rootstocks
  • mirtilo: Cutting blueberry data
  • orchard: Orchard data
  • passiflora: Substrate data in the production of passion fruit seedlings
  • pepper: Pepper data
  • phao: Osmocote in Phalaenopsis sp.
  • pomegranate: Pomegranate data
  • porco: Pig development and production
  • sensorial: Sensorial data
  • simulate1: Simulated data dict
  • simulate2: Simulated data dbct
  • simulate3: Simulated data dqlt
  • soybean: Soybean data
  • tomate: Tomato data
  • weather: Weather data

Descritive analysis

  • desc: Descriptive analysis
  • desc2fat: Descriptive analysis (Two factors)
  • desc3fat: Descriptive analysis (Three factors)
  • dispvar: Boxplot with standardized data
  • tabledesc: Table descritive analysis

Analysis function

t test to compare means with a reference value

  • tonetest: t test to compare means with a reference value

Analysis for testing of two independent or dependent samples by parametric or non-parametric method

  • test_two: Test for two samples

Analysis of simple experiments

  • DIC: Completely randomized design
  • DBC: Randomized block design
  • DQL: Latin square design

Analysis of simple experiments with an additional treatment for quantitative factor

  • dic.ad: Completely randomized design with an additional treatment for quantitative factor
  • dbc.ad: Randomized block design with an additional treatment for quantitative factor

Analysis of simple experiments in DIC and DBC by generalized linear model (Binomial or Poisson)

  • DIC.glm: Completely randomized design by glm
  • DBC.glm: Randomized block design by glm

Analysis of experiments in DIC, DBC or DQL with multiple assessments over time or disregarding the effect of another factor

  • DICT: Completely randomized design evaluated over time
  • DBCT: Randomized block design evaluated over time
  • DQLT: Latin square design evaluated over time

Analysis of groups of experiments in DIC and DBC

  • conjdbc: Joint analysis of experiments in randomized block design
  • conjdic: Joint analysis of experiments in completely randomized design

Analysis of groups of experiments in FAT2DBC

  • conjfat2dbc: Joint analysis of experiments in randomized block design in double factorial

Analysis of experiments in double factorial design in DIC and DBC

  • FAT2DIC: DIC experiments in double factorial
  • FAT2DBC: DBC experiments in double factorial

Analysis of double factorial design experiments in DIC or DBC with an additional treatment

  • FAT2DIC.ad: DIC experiment in double factorial design with an additional treatment
  • FAT2DBC.ad: DBC experiment in double factorial design with an additional treatment

Analysis of DIC or DBC experiments in a factorial scheme with three factors

  • FAT3DIC: DIC experiments in triple factorial
  • FAT3DBC: DBC experiments in triple factorial

Analysis of triple factorial design experiments in DIC or DBC with an additional treatment

  • FAT3DIC.ad: DIC experiment in double factorial design with an additional treatment
  • FAT3DBC.ad: DBC experiment in double factorial design with an additional treatment

Split-plot scheme in DIC or DBC

  • PSUBDBC: DBC experiments in split-plot
  • PSUBDIC: DIC experiments in split-plot

Splitsplitplot parcels scheme in DBC

  • PSUBSUBDBC: DBC experiments in split-split-plot

Plot subdivided into randomized blocks with a subplot in a double factorial scheme

  • PSUBFAT2DBC: Plot subdivided into randomized blocks with a subplot in a double factorial scheme

Dunnett's Test for Comparison of Control vs. Treatments

  • dunnett: Dunnett test

Dunn's non-parametric test

  • dunn: Dunn test

Logistic regression 3 or 4 parameters

  • logistic: Logistic regression

Polynomial Regression to the Third Degree

  • polynomial: Linear regression graph
  • polynomial2: Linear regression graph in double factorial
  • polynomial2_color: Linear regression graph in double factorial with color graph

Principal component analysis

  • PCA_function: Principal components analysis

Graphs

  • barfacet: Bar graph for one factor with facets
  • bargraph_onefactor: Group DIC, DBC and DQL functions column charts
  • bargraph_twofactor: Group FAT2DIC, FAT2DBC, PSUBDIC or PSUBDBC functions column charts
  • barplot_positive: Positive barplot
  • bar_dunnett: Barplot for Dunnett test
  • bar_graph: Bar graph for one factor
  • bar_graph2: Bar graph for one factor model 2
  • corgraph: Correlogram
  • cor_ic: Plot Pearson correlation with interval of confidence
  • ibarplot.double: Invert letters for two factor chart
  • line_plot: Line chart
  • plot_cor: Plot correlation
  • plot_interaction: Interaction plot
  • plot_jitter: Column, box or segment chart with observations
  • plot_TH: Climate chart of temperature and humidity
  • plot_TH1: Climate chart of temperature and humidity (Model 2)
  • radargraph: Circular column chart
  • seg_graph: Segment graph for one factor
  • seg_graph2: Point graph for one factor model 2
  • sk_graph: Scott-Knott graphics
  • spider_graph: Spider graph for sensorial analysis
  • TBARPLOT.reverse: Reverse graph of DICT, DBCT and DQL output when geom="bar"
  • plot_tonetest: Graphic for t test to compare means with a reference value

Utils

  • sketch: Experimental sketch
  • aacp: Area under the curve
  • transf: Data transformation (Box-Cox, 1964)
  • summarise_anova: Summary of analysis of variance and test of means
  • summarise_dunnett: Dunnett's Test Summary
  • confinterval: Interval of confidence for groups

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Version

Install

install.packages('AgroR')

Monthly Downloads

1,167

Version

1.3.7

License

GPL (>= 2)

Maintainer

Gabriel Danilo Shimizu

Last Published

July 2nd, 2025

Functions in AgroR (1.3.7)

PSUBDBC

Analysis: DBC experiments in split-plot
PSUBDIC

Analysis: DIC experiments in split-plot
PCA_function

Analysis: Principal components analysis
FAT3DBC.ad

Analysis: DBC experiments in triple factorial with aditional
FAT2DIC

Analysis: DIC experiments in double factorial
FAT2DIC.ad

Analysis: DIC experiment in double factorial design with an additional treatment
FAT3DBC

Analysis: DBC experiments in triple factorial
FAT2DBC.ad

Analysis: DBC experiment in double factorial design with an additional treatment
FAT3DIC.ad

Analysis: DIC experiments in triple factorial with aditional
FAT3DIC

Analysis: DIC experiments in triple factorial
bar_dunnett

Graph: Barplot for Dunnett test
barfacet

Graph: Bar graph for one factor with facets
bar_graph2

Graph: Bar graph for one factor model 2
PSUBSUBDBC

Analysis: DBC experiments in split-split-plot
bar_graph

Graph: Bar graph for one factor
aacp

Utils: Area under the curve
PSUBFAT2DBC

Analysis: Plot subdivided into randomized blocks with a subplot in a double factorial scheme
STRIPLOT

Analysis: DBC experiments in strip-plot
TBARPLOT.reverse

Graph: Reverse graph of DICT, DBCT and DQL output when geom="bar"
aristolochia

Dataset: Germination of seeds of Aristolochia sp. as a function of temperature.
bargraph_onefactor

Graph: Group DIC, DBC and DQL functions column charts
cloro

Dataset: Sodium dichloroisocyanurate in soybean
barplot_positive

Graph: Positive barplot
bean

Dataset: Bean
bargraph_twofactor

Graph: Group FAT2DIC, FAT2DBC, PSUBDIC or PSUBDBC functions column charts
cor_ic

Graph: Plot Pearson correlation with interval of confidence
conjfat2dbc

Analysis: Joint analysis of experiments in randomized block design in scheme factorial double
conjdic

Analysis: Joint analysis of experiments in completely randomized design
conjdbc

Analysis: Joint analysis of experiments in randomized block design
corgraph

Graph: Correlogram
corn

Dataset: Corn
dic.ad

Analysis: Completely randomized design with an additional treatment for quantitative factor
dispvar

Descriptive: Boxplot with standardized data
fat2_table

Utils: Summary of the analysis for factor arrangement with two qualitative factors.
confinterval

Utils: Interval of confidence for groups
desd_fat2_quant_ad

Analysis: Regression analysis by orthogonal polynomials for double factorial scheme with additional control
eucalyptus

Dataset: Eucaliptus grandis Barbin (2013)
grid.onefactor

utils: group graphs of the output of simple experiments in dic, dbc or dql
ibarplot.double

Graph: Invert letters for two factor chart
desc3fat

Descriptive: Descriptive analysis (Three factors)
jointcluster

Analysis: Method to evaluate similarity of experiments based on QMres
laranja

Dataset: Orange plants under different rootstocks
phao

Dataset: Osmocote in Phalaenopsis sp.
plot_cor

Graph: Plot correlation
plot_TH1

Graph: Climate chart of temperature and humidity (Model 2)
plot_TH

Graph: Climate chart of temperature and humidity
emerg

Dataset: Emergence of passion fruit seeds over time .
dunnett

Analysis: Dunnett test
dunn

Analysis: Post-hoc Dunn
orchard

Dataset: Orchard
mirtilo

Dataset: Cutting blueberry data
covercrops

Dataset: Covercrops
enxofre

Dataset: Sulfur data
dbc.ad

Analysis: Randomized block design with an additional treatment for quantitative factor
pepper

Dataset: Pepper
passiflora

Dataset: Substrate data in the production of passion fruit seedlings
porco

Dataset: Pig development and production
pomegranate

Dataset: Pomegranate data
desc2fat

Descriptive: Descriptive analysis (Two factors)
plot_interaction

Graph: Interaction plot
desc

Descriptive: Descriptive analysis
simulate1

Dataset: Simulated data dict
simulate2

Dataset: Simulated data dbct
sk_graph

Graph: Scott-Knott graphics
plot_tonetest

Graphics: Graphic for t test to compare means with a reference value
simulate3

Dataset: Simulated data dqlt
line_plot

Graph: Line chart
test_two

Analysis: Test for two samples
polynomial

Analysis: Linear regression graph
seg_graph

Graph: Point graph for one factor
spider_graph

Graph: Spider graph for sensorial analysis
plot_jitter

Graph: Column, box or segment chart with observations
quant.fat2.desd

Analysis: Polynomial splitting for double factorial in DIC and DBC
tabledesc

Descriptive: Table descritive analysis
transf

Utils: Data transformation (Box-Cox, 1964)
sketch

Utils: Experimental sketch
summarise_dunnett

Utils: Dunnett's Test Summary
polynomial2

Analysis: Linear regression graph in double factorial
summarise_conj

Utils: Summary of Analysis of Variance and Test of Means for Joint analysis
soybean

Dataset: Soybean
logistic

Analysis: Logistic regression
seg_graph2

Graph: Point graph for one factor model 2
summarise_anova

Utils: Summary of Analysis of Variance and Test of Means
sensorial

Dataset: Sensorial data
tonetest

Analysis: t test to compare means with a reference value
tomate

Dataset: Tomato data
polynomial2_color

Analysis: Linear regression graph in double factorial with color graph
weather

Dataset: Weather data
AgroR-package

AgroR: Experimental Statistics and Graphics for Agricultural Sciences
DBC.glm

Analysis: Randomized block design by glm
DIC.glm

Analysis: Completely randomized design by glm
DIC

Analysis: Completely randomized design
DQL

Analysis: Latin square design
DQLT

Analysis: Latin square design evaluated over time
DBCT

Analysis: Randomized block design evaluated over time
DBC

Analysis: Randomized block design
DICT

Analysis: Completely randomized design evaluated over time
FAT2DBC

Analysis: DBC experiments in double factorial