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metan (version 1.11.0)

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

3,544

Version

1.11.0

License

GPL-3

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Repository

https://github.com/TiagoOlivoto/metan

Maintainer

Tiago Olivoto

Last Published

December 12th, 2020

Functions in metan (1.11.0)

Schmildt's genotypic confidence index

Fast way to create bar plots

Genotype analysis by fixed-effect models

correlated_vars

Generate correlated variables

Correlation between stability indexes

Coerce to an object of class lpcor

Find possible outliers in a dataset

Generate a covariance matrix

Get a distance matrix

Mantel test for a set of correlation matrices

Mahalanobis Distance

non_collinear_vars

Select a set of predictors with minimal multicollinearity

Linear and Partial Correlation Coefficients

Adjusted Coefficient of Variation

Create a correlation heat map

plot.correlated_vars

Plot an object of class correlated_vars

Within-environment analysis of variance

Visualization of a correlation matrix

Plot the eigenvalues

Print an object of class Fox

Several types of residual plots

Several types of residual plots

print.Annicchiarico

Print an object of class Annicchiarico

Plot the confidence interval for correlation

print.ecovalence

Print an object of class ecovalence

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

print.env_dissimilarity

Print an object of class env_dissimilarity

Rescale a variable to have specified minimum and maximum values

Multi-environment trial of oat

Several types of residual plots

Multi-environment trial of maize

Personalized theme for ggplot2-based graphics

Weighting between stability and mean performance

Weighted Average of Absolute Scores

Tidy eval helpers

Cluster genotypes or environments

Eberhart and Russell's regression model

Power Law Residuals as yield stability index

Details for genotype-environment trials

Data for examples

Multi-Environment Trial Analysis

Fox's stability function

Variance-covariance matrices for designed experiments

Huehn's stability statistics

Cross-validation procedure

env_stratification

Environment stratification

Alternative to dplyr::do for doing anything

Descriptive statistics

Multi-trait selection index

Smith-Hazel index

Thennarasu's stability statistics

Several types of residual plots

plot.anova_joint

Several types of residual plots

Joint analysis of variance

Genotype-environment means

Graphical analysis of genotype-vs-environment interaction

Several types of residual plots

Plot the Smith-Hazel index

Plot the response surface model

Arrange separate ggplots into the same graphic

Predict method for gamem fits

print.colindiag

Print an object of class colindiag

Predict a two-way table based on GGE model

print.corr_coef

Print an object of class corr_coef

Print an object of class ge_stats

Collinearity Diagnostics

Get data from a model easily

Genotype plus genotype-by-environment model

Pairwise combinations of variables

Data from an alpha lattice design

AMMI-based stability indexes

Annicchiarico's genotypic confidence index

Clustering analysis

coincidence_index

Computes the coincidence index of genotype selection

Single maize trial

Mahalanobis distance from designed experiments

Plot the multi-trait stability index

Two-way table to a 'long' format

plot.performs_ammi

Several types of residual plots

Genotype-environment analysis by mixed-effect models

Cross-validation procedure

Make a two-way table

Coerce to an object of class lpcor

Genotype-environment effects

Plots an object of class can_cor

Stability analysis and environment stratification

Adjusted Coefficient of Variation as yield stability index

Data for examples

Print the partial correlation coefficients

Print an object of class Shukla

print.Thennarasu

Print an object ofclass Thennarasu

Print an object of class waas

Print an object of class waasb

print.env_stratification

Print the env_stratification model

print.waas_means

Print an object of class waas_means

Print an object of class gamem

Selects a best subset of predictor variables.

Response surface model

plot.clustering

Plot an object of class clustering

Cross-validation procedure

Genotype-environment winners

Shukla's stability variance parameter

Canonical correlation analysis

Bind cross-validation objects

Confidence interval for correlation coefficient

Generate normal, correlated variables

impute_missing_val

Missing value imputation

Check for common errors in multi-environment trial data

Computes Pearson's correlation matrix with p-values

Stability analysis based on Wricke's model

plot.ge_cluster

Plot an object of class ge_cluster

plot.ge_effects

Plot an object of class ge_effects

Combines data.frames by row filling missing values

utils_rows_cols

Utilities for handling with rows and columns

Lin e Binns' superiority index

Generate significance stars from p-values

Utilities for set operations for many sets

Utilities for handling with classes

Encode variables to a specific format

Plot the BLUPs for genotypes

print.AMMI_indexes

Print an object of class AMMI_indexes

Plot heat maps with genotype ranking

Predict method for waasb fits

is_balanced_trial

Check if a data set is balanced

Geometric adaptability index

env_dissimilarity

Dissimilarity between environments

Genotype analysis by mixed-effect models

Fast way to create line plots

Genotype-Ideotype Distance Index

Print an object of class can_cor

Genotype by trait biplot

Simulate genotype-environment data

Statistics for genotype-vs-environment interaction

print.coincidence

Print an object of class coincidence

Path coefficients with minimal multicollinearity

Additive Main effects and Multiplicative Interaction

Genotype by yield*trait biplot

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

Print an object of class sh

plot.env_dissimilarity

Plot an object of class env_dissimilarity

Plot an object of class ge_reg

plot.ge_factanal

Plot the ge_factanal model

Utilities for data Copy-Pasta

Useful functions for computing descriptive statistics

Utilities for handling with matrices

Draw Venn diagrams

print.superiority

Print an object ofclass superiority

Multi-trait selection index

plot.env_stratification

Plot the env_stratification model

Multi-trait stability index

predict.performs_ammi

Predict the means of a performs_ammi object

Create GGE, GT or GYT biplots

Plot the multi-trait genotype-ideotype distance index

print.anova_ind

Print an object of class anova_ind

Predict the means of a waas object

print.anova_joint

Print an object of class anova_joint

Print an object of class Schmildt

Plot scores in different graphical interpretations

Plot WAASBY values for genotype ranking

Print an object ofclass Huehn

print.ge_factanal

Print an object of class ge_factanal

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 ge_reg

Objects exported from other packages

Reorder a correlation matrix

Print an object of class mtsi

Utilities for handling with NA and zero values

Utilities for handling with numbers and strings

print.performs_ammi

Print an object of class performs_ammi

Tukey Honest Significant Differences

Pseudoinverse of a square matrix

Split a data frame by factors

print.path_coeff

Print an object of class path_coeff

Transpose a data frame

Weighted Average of Absolute Scores

Weighted Average of Absolute Scores

Resende_indexes

Stability indexes based on a mixed-effect model