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metan (version 1.18.0)

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

3,307

Version

1.18.0

License

GPL-3

Issues

Pull Requests

Stars

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Repository

https://github.com/TiagoOlivoto/metan

Maintainer

Tiago Olivoto

Last Published

March 5th, 2023

Functions in metan (1.18.0)

Schmildt's genotypic confidence index

Fox's stability function

AMMI-based stability indexes

Thennarasu's stability statistics

Shukla's stability variance parameter

Huehn's stability statistics

Adjusted Coefficient of Variation

Annicchiarico's genotypic confidence index

Smith-Hazel index

Joint analysis of variance

Within-environment analysis of variance

Arrange separate ggplots into the same graphic

Fast way to create bar plots

Clustering analysis

Bind cross-validation objects

Canonical correlation analysis

Coerce to an object of class lpcor

Stability indexes based on a mixed-effect model

coincidence_index

Computes the coincidence index of genotype selection

Visualization of a correlation matrix

Pairwise combinations of variables

correlated_vars

Generate correlated variables

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

Confidence interval for correlation coefficient

Focus on section of a correlation matrix

Collinearity Diagnostics

Linear and partial correlation coefficients

Variance-covariance matrices for designed experiments

Correlation between stability indexes

Data from an alpha lattice design

Cross-validation procedure

Simulate genotype and genotype-environment data

Cross-validation procedure

Cross-validation procedure

Alternative to dplyr::do for doing anything

Descriptive statistics

Single maize trial

Multi-environment trial of oat

Multi-environment trial of maize

Genotype-environment analysis by mixed-effect models

env_stratification

Environment stratification

Adjusted Coefficient of Variation as yield stability index

Geometric adaptability index

Stability analysis based on Wricke's model

Multi-trait selection index

env_dissimilarity

Dissimilarity between environments

Find possible outliers in a dataset

Genotype analysis by mixed-effect models

Genotype analysis by fixed-effect models

Power Law Residuals as yield stability index

Eberhart and Russell's regression model

Cluster genotypes or environments

Stability analysis and environment stratification

Genotype-environment means

Details for genotype-environment trials

Graphical analysis of genotype-vs-environment interaction

Genotype-environment effects

Parametric and non-parametric stability statistics

Genotype-environment winners

Get a distance matrix

impute_missing_val

Missing value imputation

Genotype plus genotype-by-environment model

Generate a covariance matrix

Get data from a model easily

Check for common errors in multi-environment trial data

Generate normal, correlated variables

Genotype by trait biplot

Genotype by yield*trait biplot

Data for examples

Two-way table to a 'long' format

Fast way to create line plots

Mahalanobis Distance

Make a two-way table

Linear and Partial Correlation Coefficients

Data for examples

Mahalanobis distance from designed experiments

is_balanced_trial

Check if a data set is balanced

Coerce to an object of class lpcor

Multitrait Genotype-Ideotype Distance Index

Mean performance and stability in multi-environment trials

non_collinear_vars

Select a set of predictors with minimal multicollinearity

Mantel test for a set of correlation matrices

Path coefficients with minimal multicollinearity

Multi-Environment Trial Analysis

Multi-trait mean performance and stability index

Additive Main effects and Multiplicative Interaction

Multi-trait stability index

Create a correlation heat map

Multi-trait selection index

Plots an object of class can_cor

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

Network plot of a correlation matrix

plot.env_dissimilarity

Plot an object of class env_dissimilarity

plot.clustering

Plot an object of class clustering

plot.correlated_vars

Plot an object of class correlated_vars

plot.env_stratification

Plot the env_stratification model

plot.anova_joint

Several types of residual plots

Several types of residual plots

plot.ge_effects

Plot an object of class ge_effects

plot.ge_cluster

Plot an object of class ge_cluster

plot.ge_factanal

Plot the ge_factanal model

Plot an object of class ge_reg

Plot the multi-trait genotype-ideotype distance index

Create GGE, GT or GYT biplots

Several types of residual plots

Plot the multi-trait stability index

Plot the multi-trait stability index

Plot heat maps with genotype ranking

plot.performs_ammi

Several types of residual plots

plot.path_coeff

Plots an object of class path_coeff

Plot the BLUPs for genotypes

Plot the Smith-Hazel index

Plot the response surface model

Several types of residual plots

Several types of residual plots

Plot the confidence interval for correlation

Plot the eigenvalues

Print an object of class Fox

Print an object ofclass Huehn

print.Annicchiarico

Print an object of class Annicchiarico

Predict method for waasb fits

Predict the means of a waas object

predict.performs_ammi

Predict the means of a performs_ammi object

Plot scores in different graphical interpretations

Plot WAASBY values for genotype ranking

Predict a two-way table based on GGE model

Predict method for gamem fits

print.coincidence

Print an object of class coincidence

Print an object of class can_cor

print.corr_coef

Print an object of class corr_coef

print.colindiag

Print an object of class colindiag

Print an object of class Schmildt

Print an object of class Shukla

Print an object of class ge_stats

Print an object of class mtmps

print.env_stratification

Print the env_stratification model

print.anova_joint

Print an object of class anova_joint

print.performs_ammi

Print an object of class performs_ammi

print.ge_factanal

Print an object of class ge_factanal

Print an object of class ge_reg

Print the partial correlation coefficients

print.anova_ind

Print an object of class anova_ind

print.waas_means

Print an object of class waas_means

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 an object of class gamem

Print an object of class waasb

Print an object of class sh

Objects exported from other packages

print.ecovalence

Print an object of class ecovalence

print.Thennarasu

Print an object ofclass Thennarasu

print.ammi_indexes

Print an object of class ammi_indexes

Split a data frame by factors

Pseudoinverse of a square matrix

Personalized theme for ggplot2-based graphics

Reorder a correlation matrix

Tidy eval helpers

print.path_coeff

Print an object of class path_coeff

print.env_dissimilarity

Print an object of class env_dissimilarity

Print an object of class mtsi

Helper function for binding rows

Encode variables to a specific format

Print an object of class waas

print.superiority

Print an object ofclass superiority

Utilities for data Copy-Pasta

Utilities for handling with classes

Transpose a data frame

Response surface model

Selects a best subset of predictor variables.

Tukey Honest Significant Differences

Draw Venn diagrams

Utilities for text progress bar in the terminal

utils_rows_cols

Utilities for handling with rows and columns

Weighted Average of Absolute Scores

Rescale a variable to have specified minimum and maximum values

Several types of residual plots

Utilities for handling with numbers and strings

Utilities for handling with NA and zero values

Weighting between stability and mean performance

Useful functions for computing descriptive statistics

Set and get the Working Directory quicky

Weighted Average of Absolute Scores

Weighted Average of Absolute Scores

Utilities for data organization

Lin e Binns' superiority index

Generate significance stars from p-values

Utilities for handling with matrices

Random Sampling

Utilities for set operations for many sets