Learn R Programming

⚠️There's a newer version (1.3-7) of this package.Take me there.

agricolae (version 1.2-0)

Statistical Procedures for Agricultural Research

Description

Agricolae was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, mention Systems Engineering, Faculty of Industrial and Systems Engineering, National Engineering University (UNI), Lima-Peru. Original idea, support and data sets came from CIP (International Potato Center). Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.

Copy Link

Version

Install

install.packages('agricolae')

Monthly Downloads

34,553

Version

1.2-0

License

GPL

Maintainer

Felipe Mendiburu

Last Published

June 30th, 2014

Functions in agricolae (1.2-0)

Data of AUDPC for nonparametrical stability analysis

Finding the Kurtosis coefficient

Join class for histogram

Data Potato Wild

Data AUDPC Comas - Oxapampa

Multiple comparisons, "Least significant difference" and Adjust P-values

Data Line by tester

Data Glycoalkaloids

Coefficient of the experiment variation

Calculating the absolute or relative value of the AUDPC

Finding the Variance Analysis of the Balanced Incomplete Block Design

Data of Ralstonia population in clay soil

Plotting the multiple comparison of means

Randomized Balanced Incomplete Block Designs. BIB

Uniformity soil. Smith's Index of Soil Heterogeneity

Strip Plot Design

Line x Tester Analysis

Correlation analysis. Methods of Pearson, Spearman and Kendall

Coefficient of the similarity matrix variation

Finding the skewness coefficient

Completely Randomized Design

Finding the Variance Analysis of the Augmented block Design

Split Plot Design

Multiple comparisons. The van der Waerden (Normal Scores)

Plotting the standard error or standard deviance of a multiple comparison of means

Data of Grain yield of rice variety IR8

Data for Friedman test

Data of Bacterial Wilt (AUDPC) and soil

Random generation by Montecarlo

Data of Paracsho biodiversity

Splip-Plot analysis

Data clones from the PLRV population

Randomized Complete Block Design

groups of hclust

Omitting the rows or columns with missing observations of a matrix (NA)

Design of experiments for a factorial

Multiple comparisons, scheffe

Matrix of similarity in binary data

Augmented block design

Nonadditivity model test

Homologation of regressions

Ordering the treatments according to the multiple comparison

Data for an analysis in split-plot

Data of assessment of the population in the soil R.solanacearum

North Carolina Designs I, II and III

Multiple comparisons: Tukey

Correlation Coefficient

Data of potato yield in a different environment

Setting the last character of a chain

Normal curve on the histogram

Data of molecular markers

Data for the analysis of carolina genetic design

Class intervals for a histogram, the rule of Sturges

Data amendment Carhuaz 2006

Data evaluation of the disease overtime

Data in greenhouse

Data of sweetpotato yield

Correlation of Kendall

Data of yield of melon in a Latin square experiment

Data of native potato

frequency Table of a Histogram

Data of soil analysis for 13 localities

simulation.model

Simulation of the linear model under normality

Variance K, ties, Kendall

order plot in serpentine

consensus of clusters

Alpha design type (0,1)

Data of potato, Heterosis

Data growth of trees

Data for AMMI without repetition

Split-split-Plot analysis

Data and analysis Mother and baby trials

Analysis of the Partially Balanced Incomplete Block Design

Interpolation for nonequidistant points in matrix

Cut tree of consensus

Friedman test and multiple comparison of treatments

plot.graph.freq

Biodiversity Index

The polygon of frequency on the histogram

stability.nonpar

Nonparametric stability analysis

Strip-Plot analysis

Statistics of data grouped by factors

Multiple comparisons, Waller-Duncan

Computations of Bayesian t-values for multiple comparisons

Descriptive measures of grouped data

summary.graph.freq

frequency Table of a Histogram

Data for late blight of potatoes

Data amendment Huanuco 2006

Student-Newman-Keuls (SNK)

Graeco - latin square design

Lattice designs

Plotting the ogive from a histogram

Durbin test and multiple comparison of treatments

Grouping the treatments averages in a comparison with a minimum value

Resampling to find the optimal number of markers

resampling.model

Resampling for linear models

Stability analysis. SHUKLA'S STABILITY VARIANCE AND KANG'S

Completing missing data of a matrix according to a model

agricolae-package

Statistical Procedures for Agricultural Research

Latin Square Design

Class intervals

Duncan's new multiple range test

Data: Rainfall thresholds as support for timing fungicide applications in the control of potato late blight in Peru

Kruskal Wallis test and multiple comparison of treatments.

LATEBLIGHT - Simulator for potato late blight Version LB2004

Data of cutting