Learn R Programming

⚠️There's a newer version (1.19.0) of this package.Take me there.

metan (version 1.5.1)

Multi Environment Trials Analysis

Description

Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) , Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) , joint Regression Analysis by Eberhart & Russel (1966) (), ecovalence by Wricke (1965), genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method , stability variance by Shukla (1972) , weighted average of absolute scores by Olivoto et al. (2019a) , and multi-trait stability index by Olivoto et al. (2019b) . Non-parametric methods includes superiority index by Lin & Binns (1988) , nonparametric measures of phenotypic stability by Huehn (1990) , TOP third statistic by Fox et al. (1990) , geometric adaptability index described by Shahbazi (2019) . Functions for computing biometrical analysis such as path analysis, canonical correlation, partial correlation, clustering analysis, and tools for inspecting, manipulating, summarizing and plotting typical multi-environment trial data are also provided.

Copy Link

Version

Install

install.packages('metan')

Monthly Downloads

2,706

Version

1.5.1

License

GPL-3

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/TiagoOlivoto/metan

Maintainer

Tiago Olivoto

Last Published

April 25th, 2020

Functions in metan (1.5.1)

Annicchiarico's genotypic confidence index

Huehn's stability statistics

Fox's stability function

Thennarasu's stability statistics

Within-environment analysis of variance

Shukla's stability variance parameter

Resende_indexes

Stability indexes based on a mixed-effect model

AMMI-based stability indexes

Schmildt's genotypic confidence index

Coerce to an object of class lpcor

Bind cross-validation objects

Cross-validation procedure

Confidence interval for correlation coefficient

Pairwise combinations of variables

Joint analysis of variance

Arrange multiple ggplot2 graphics in a single image window

Sample size planning for a desired Pearson's correlation confidence interval

Variance-covariance matrices for designed experiments

Cross-validation procedure

Fast way to create bar plots

Correlation between stability indexes

Multi-trait selection index

Geometric adaptability index

Genotype analysis by fixed-effect models

Clustering analysis

Genotype analysis by mixed-effect models

Data for examples

Genotype-environment analysis by mixed-effect models

Statistics for genotype-vs-environment interaction

Find possible outliers in a dataset

Eberhart and Russell's regression model

Collinearity Diagnostics

is_balanced_trial

Check if a data set is balanced

Fast way to create line plots

Canonical correlation analysis

Computes Pearson's correlation matrix with p-values

Cross-validation procedure

Data from an alpha lattice design

Stability analysis based on Wricke's model

Genotype-Ideotype Distance Index

Coerce to an object of class lpcor

Multi-Environment Trial Analysis

Visualization of a correlation matrix

Cluster genotypes or environments

env_dissimilarity

Dissimilarity between environments

Details for genotype-environment trials

Descriptive statistics

Get data from a model easily

Genotype-environment winners

Multi-trait stability index

Single maize trial

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

plot.env_dissimilarity

Plot an object of class env_dissimilarity

Mahalanobis distance from designed experiments

Alternative to dplyr::do for doing anything

non_collinear_vars

Select a set of predictors with minimal multicollinearity

Genotype-environment means

Graphical analysis of genotype-vs-environment interaction

Multi-environment trial of oat

plot.clustering

Plot an object of class clustering

Create a correlation heat map

Two-way table to a 'long' format

Multi-trait selection index

Several types of residual plots

Several types of residual plots

plot.ge_cluster

Plot an object of class ge_cluster

Genotype-environment effects

Stability analysis and environment stratification

Plot heat maps with genotype ranking

impute_missing_val

Missing value imputation

Check for common errors in multi-environment trial data

Genotype by trait biplot

Genotype plus genotype-by-environment model

Several types of residual plots

Mantel test for a set of correlation matrices

Several types of residual plots

Plot the BLUPs for genotypes

Multi-environment trial of maize

predict.performs_ammi

Predict the means of a performs_ammi object

Predict the means of a waas object

Print an object of class ge_reg

print.colindiag

Print an object of class colindiag

Print an object of class can_cor

print.ge_factanal

Print an object of class ge_factanal

Combines data.frames by row filling missing values

print.Annicchiarico

Print an object of class Annicchiarico

Linear and Partial Correlation Coefficients

Make a two-way table

Path coefficients with minimal multicollinearity

Print an object of class Fox

Data for examples

Print an object of class Shukla

Mahalanobis Distance

print.Thennarasu

Print an object ofclass Thennarasu

Utilities for handling with classes

Print an object of class mgidi Print a mgidi object in two ways. By default, the results are shown in the R console. The results can also be exported to the directory.

Utilities for handling with matrices

Print an object of class mtsi

Objects exported from other packages

plot.ge_effects

Plot an object of class ge_effects

plot.ge_factanal

Plot the ge_factanal model

Plot the confidence interval for correlation

plot.anova_joint

Several types of residual plots

Reorder a correlation matrix

utils_rows_cols

Utilities for handling with rows and columns

Additive Main effects and Multiplicative Interaction

Plots an object of class can_cor

Useful functions for computing descriptive statistics

Plot an object of class ge_reg

Rescale a variable to have specified minimum and maximum values

Predict method for gamem fits

Plot the eigenvalues

Predict a two-way table based on GGE model

print.anova_ind

Print an object of class anova_ind

Personalized theme for ggplot2-based graphics

print.anova_joint

Print an object of class anova_joint

Create GGE biplots

plot.performs_ammi

Several types of residual plots

Print an object of class Schmildt

Print an object ofclass Huehn

Plot the response surface model

Print the partial correlation coefficients

Print an object of class ge_stats

print.waas_means

Print an object of class waas_means

Print an object of class waasb

Tidy eval helpers

Plot the multi-trait genotype-ideotype distance index

Plot the multi-trait stability index

Plot WAASBY values for genotype ranking

Plot scores in different graphical interpretations

Predict method for waasb fits

Print an object of class gamem

print.superiority

Print an object ofclass superiority

print.env_dissimilarity

Print an object of class env_dissimilarity

Encode variables to a factor

Tukey Honest Significant Differences

Print an object of class waas

Pseudoinverse of a square matrix

Split a data frame by factors

print.corr_coef

Print an object of class corr_coef

print.AMMI_indexes

Print an object of class AMMI_indexes

print.path_coeff

Print an object of class path_coeff

Generate significance stars from p-values

print.performs_ammi

Print an object of class performs_ammi

print.ecovalence

Print an object of class ecovalence

Several types of residual plots

Response surface model

Lin e Binns' superiority index

Utilities for handling with NA values

Utilities for handling with numbers and strings

Weighted Average of Absolute Scores

Weighted Average of Absolute Scores

Weighted Average of Absolute Scores

Weighting between stability and mean performance