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agricolae (version 1.0-6)

Statistical Procedures for Agricultural Research

Description

Agricolae is a project in order to obtain the degree of master in Systems Engineering in the National University of Engineering in Lima-Peru (UNI in Spanish). These functions are currently utilized by the International Potato Center Research (CIP), the Universidad Nacional Agraria La Molina (UNALM-PERU), and the Instituto Nacional de Investigacion Agricola (INIA-PERU). It comprises the functionality of statistical analysis into experimental designs applied specially for field experiments in agriculture and plant breeding: Lattice, factorial, complete and incomplete block, Latin Square, Greaco, Alpha designs, Cyclic designs, comparison of multi-location trials, comparison between treatments, resampling, simulation, biodiversity indexes and consensus cluster.

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Version

Install

install.packages('agricolae')

Monthly Downloads

28,504

Version

1.0-6

License

GPL

Maintainer

Felipe Mendiburu

Last Published

October 22nd, 2023

Functions in agricolae (1.0-6)

agricolae-package

Statistical Procedures for Agricultural Research

Kruskal Wallis test and multiple comparison of treatments.

simulation.model

Simulation of the linear model under normality

Nonadditivity model test

Setting the last character of a chain

groups of hclust

Uniformity soil. Smith's Index of Soil Heterogeneity

Data amendment Huanuco 2006

Data of soil analysis for 13 localities

Calculating the absolute or relative value of the AUDPC

Data AUDPC Comas - Oxapampa

Factorial design k-factors with n-levels in blocks

Coefficient of the experiment variation

Data of molecular markers

Data growth of trees

Biodiversity Index

Lattice designs

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

Finding the Kurtosis coefficient

Data for an analysis in split-plot

Data Glycoalkaloids

Multiple comparisons. The van der Waerden (Normal Scores)

Randomizing a factorial in a block

Finding the Variance Analysis of the Balanced Incomplete Block Design

Data for AMMI without repetition

Randomized Complete Block Design

Graeco - latin square design

Interpolation for nonequidistant points in matrix

Resampling to find the optimal number of markers

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

Data for the analysis of carolina genetic design

Data for late blight of potatoes

Data amendment Carhuaz 2006

Multiple comparisons: Tukey

Data for Friedman test

Data of native potato

Data of Ralstonia population in clay soil

consensus of clusters

Alpha design type (0,1)

resampling.model

Resampling for linear models

Plotting the multiple comparison of means

Matrix of similarity in binary data

Data of potato, Heterosis

Class intervals

Data of Grain yield of rice variety IR8

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

Data clones from the PLRV population

Data of sweetpotato yield

Data of potato yield in a different environment

Completing missing data of a matrix according to a model

Homologation of regressions

Friedman test and multiple comparison of treatments

Data Line by tester

Variance K, ties, Kendall

Randomized Balanced Incomplete Block Designs. BIB

Cut tree of consensus

Design in blocks for factorial pxq

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

Random generation by Montecarlo

Completely Randomized Design

Analysis of the Partially Balanced Incomplete Block Design

Data Potato Wild

stability.nonpar

Nonparametric stability analysis

Data of cutting

Statistics of data grouped by factors

Durbin test and multiple comparison of treatments

Line x Tester Analysis

Plotting the ojiva from a histogram

Data evaluation of the disease overtime

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

North Carolina Designs I, II and III

Frequency Table of a Histogram

Data of Bacterial Wilt (AUDPC) and soil

Data and analysis Mother and baby trials

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

Join class for histogram

Coefficient of the similarity matrix variation

Class intervals for a histogram, the rule of Sturges

Normal curve on the histogram

Multiple comparisons, Waller-Duncan

Descriptive measures of grouped data

Data of yield of melon in a Latin square experiment

Latin Square Design

Data of Paracsho biodiversity

Strip-Plot analysis

Correlation Coefficient

Correlation analysis. Methods of Pearson, Spearman and Kendall

Data in greenhouse

Finding the skewness coefficient

Ordering the treatments according to the multiple comparison

The polygon of frequency on the histogram

Computations of Bayesian t-values for multiple comparisons

Grouping the treatments averages in a comparison with a minimum value

Data of yield for nonparametrical stability analysis

Correlation of Kendall