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metan (version 1.19.0)

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) , Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) , geometric adaptability index by Mohammadi & Amri (2008) , joint regression analysis by Eberhart & Russel (1966) , genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method, power law residuals (POLAR) statistics by Doring et al. (2015) , scale-adjusted coefficient of variation by Doring & Reckling (2018) , 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) . 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.

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Install

install.packages('metan')

Monthly Downloads

2,846

Version

1.19.0

License

GPL-3

Issues

Pull Requests

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Repository

https://github.com/nepem-ufsc/metan

Homepage

https://nepem-ufsc.github.io/metan/

Maintainer

Tiago Olivoto

Last Published

December 15th, 2024

Functions in metan (1.19.0)

Adjusted Coefficient of Variation

Shukla's stability variance parameter

AMMI-based stability indexes

Within-environment analysis of variance

Clustering analysis

coincidence_index

Computes the coincidence index of genotype selection

Arrange separate ggplots into the same graphic

Joint analysis of variance

Stability indexes based on a mixed-effect model

Fox's stability function

Canonical correlation analysis

Coerce to an object of class lpcor

Huehn's stability statistics

Schmildt's genotypic confidence index

Focus on section of a correlation matrix

Visualization of a correlation matrix

Collinearity Diagnostics

Pairwise combinations of variables

Correlation between stability indexes

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

Confidence interval for correlation coefficient

Bind cross-validation objects

Linear and partial correlation coefficients

Fast way to create bar plots

correlated_vars

Generate correlated variables

Variance-covariance matrices for designed experiments

Cross-validation procedure

Simulate genotype and genotype-environment data

Multi-environment trial of maize

Cross-validation procedure

Cross-validation procedure

Data from an alpha lattice design

Single maize trial

Alternative to dplyr::do for doing anything

Descriptive statistics

Multi-environment trial of oat

Multi-trait selection index

Find possible outliers in a dataset

Genotype analysis by fixed-effect models

env_dissimilarity

Dissimilarity between environments

Stability analysis based on Wricke's model

Geometric adaptability index

env_stratification

Environment stratification

Genotype-environment analysis by mixed-effect models

Genotype analysis by mixed-effect models

Adjusted Coefficient of Variation as yield stability index

Cluster genotypes or environments

Eberhart and Russell's regression model

Genotype-environment effects

Stability analysis and environment stratification

Genotype-environment means

Power Law Residuals as yield stability index

Graphical analysis of genotype-vs-environment interaction

Details for genotype-environment trials

Parametric and non-parametric stability statistics

Genotype-environment winners

Get a distance matrix

Generate normal, correlated variables

Genotype plus genotype-by-environment model

Check for common errors in multi-environment trial data

Genotype by yield*trait biplot

Generate a covariance matrix

Get data from a model easily

impute_missing_val

Missing value imputation

Data for examples

Genotype by trait biplot

Make a two-way table

Two-way table to a 'long' format

Coerce to an object of class lpcor

is_balanced_trial

Check if a data set is balanced

Mahalanobis Distance

Mahalanobis distance from designed experiments

Fast way to create line plots

Linear and Partial Correlation Coefficients

Data for examples

non_collinear_vars

Select a set of predictors with minimal multicollinearity

Mean performance and stability in multi-environment trials

Path coefficients with minimal multicollinearity

Multi-Environment Trial Analysis

Additive Main effects and Multiplicative Interaction

Mantel test for a set of correlation matrices

Multitrait Genotype-Ideotype Distance Index

Network plot of a correlation matrix

Multi-trait mean performance and stability index

Multi-trait stability index

plot.env_dissimilarity

Plot an object of class env_dissimilarity

plot.anova_joint

Several types of residual plots

Plots an object of class can_cor

plot.env_stratification

Plot the env_stratification model

plot.clustering

Plot an object of class clustering

plaisted_peterson

Stability analysis based on Plaisted and Peterson (1959)

Create a correlation heat map

plot.correlated_vars

Plot an object of class correlated_vars

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

plot.ge_effects

Plot an object of class ge_effects

Multi-trait selection index

Plot an object of class ge_reg

Plot the multi-trait genotype-ideotype distance index

Create GGE, GT or GYT biplots

plot.ge_factanal

Plot the ge_factanal model

Several types of residual plots

Several types of residual plots

Plot the multi-trait stability index

plot.ge_cluster

Plot an object of class ge_cluster

Plot the multi-trait stability index

Several types of residual plots

Plot the BLUPs for genotypes

Several types of residual plots

Plot the Smith-Hazel index

Plot heat maps with genotype ranking

plot.performs_ammi

Several types of residual plots

Plot the response surface model

Plot the confidence interval for correlation

plot.path_coeff

Plots an object of class path_coeff

predict.performs_ammi

Predict the means of a performs_ammi object

Plot the eigenvalues

Predict a two-way table based on GGE model

print.Annicchiarico

Print an object of class Annicchiarico

Plot scores in different graphical interpretations

Print an object of class Fox

Predict the means of a waas object

Predict method for waasb fits

print.coincidence

Print an object of class coincidence

print.ammi_indexes

Print an object of class ammi_indexes

print.anova_joint

Print an object of class anova_joint

print.anova_ind

Print an object of class anova_ind

print.colindiag

Print an object of class colindiag

Print an object ofclass Huehn

Plot WAASBY values for genotype ranking

Predict method for gamem fits

Print an object of class can_cor

print.Thennarasu

Print an object ofclass Thennarasu

Print an object of class Shukla

Print an object of class Schmildt

Print an object of class gamem

print.corr_coef

Print an object of class corr_coef

Print the partial correlation coefficients

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.

print.env_stratification

Print the env_stratification model

print.env_dissimilarity

Print an object of class env_dissimilarity

Print an object of class ge_reg

Print an object of class ge_stats

print.plaisted_peterson

Print an object of class plaisted_peterson

Print an object of class waasb

Print an object of class sh

print.waas_means

Print an object of class waas_means

print.ecovalence

Print an object of class ecovalence

Print an object of class mtsi

Print an object of class mtmps

print.ge_factanal

Print an object of class ge_factanal

print.superiority

Print an object ofclass superiority

Print an object of class waas

print.performs_ammi

Print an object of class performs_ammi

print.path_coeff

Print an object of class path_coeff

Pseudoinverse of a square matrix

Split a data frame by factors

Response surface model

Selects a best subset of predictor variables.

Generate significance stars from p-values

Reorder a correlation matrix

Objects exported from other packages

Lin e Binns' superiority index

Personalized theme for ggplot2-based graphics

Helper function for binding rows

Encode variables to a specific format

Tidy eval helpers

Utilities for data organization

Rescale a variable to have specified minimum and maximum values

Several types of residual plots

Utilities for handling with matrices

Tukey Honest Significant Differences

Transpose a data frame

Utilities for handling with classes

Utilities for data Copy-Pasta

Utilities for handling with NA and zero values

Set and get the Working Directory quicky

Random Sampling

Utilities for text progress bar in the terminal

Utilities for handling with numbers and strings

Utilities for set operations for many sets

Useful functions for computing descriptive statistics

utils_rows_cols

Utilities for handling with rows and columns

Weighted Average of Absolute Scores

Draw Venn diagrams

Weighting between stability and mean performance

Weighted Average of Absolute Scores

Weighted Average of Absolute Scores

Annicchiarico's genotypic confidence index

Thennarasu's stability statistics

Smith-Hazel index