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metan (version 1.6.1)

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.

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Install

install.packages('metan')

Monthly Downloads

3,307

Version

1.6.1

License

GPL-3

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Repository

https://github.com/TiagoOlivoto/metan

Maintainer

Tiago Olivoto

Last Published

June 7th, 2020

Functions in metan (1.6.1)

Schmildt's genotypic confidence index

AMMI-based stability indexes

Shukla's stability variance parameter

Thennarasu's stability statistics

Fox's stability function

Resende_indexes

Stability indexes based on a mixed-effect model

Annicchiarico's genotypic confidence index

Huehn's stability statistics

Smith-Hazel index

Canonical correlation analysis

Fast way to create bar plots

Coerce to an object of class lpcor

Arrange multiple ggplot2 graphics in a single image window

Cross-validation procedure

Cross-validation procedure

Descriptive statistics

Alternative to dplyr::do for doing anything

Joint analysis of variance

Within-environment analysis of variance

Clustering analysis

Pairwise combinations of variables

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

Correlation between stability indexes

Multi-environment trial of maize

Cluster genotypes or environments

Genotype-environment winners

Details for genotype-environment trials

Make a two-way table

Get data from a model easily

Multi-environment trial of oat

Data for examples

Genotype-environment effects

Genotype analysis by mixed-effect models

Confidence interval for correlation coefficient

Multi-trait selection index

Find possible outliers in a dataset

Genotype-environment means

Fast way to create line plots

is_balanced_trial

Check if a data set is balanced

Genotype-environment analysis by mixed-effect models

Graphical analysis of genotype-vs-environment interaction

Eberhart and Russell's regression model

plot.anova_joint

Several types of residual plots

Plots an object of class can_cor

Several types of residual plots

impute_missing_val

Missing value imputation

plot.clustering

Plot an object of class clustering

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

Create a correlation heat map

Check for common errors in multi-environment trial data

Stability analysis and environment stratification

Multi-trait stability index

non_collinear_vars

Select a set of predictors with minimal multicollinearity

Statistics for genotype-vs-environment interaction

Mahalanobis distance from designed experiments

Two-way table to a 'long' format

Stability analysis based on Wricke's model

Computes Pearson's correlation matrix with p-values

Genotype plus genotype-by-environment model

Bind cross-validation objects

Visualization of a correlation matrix

plot.env_dissimilarity

Plot an object of class env_dissimilarity

Plot the response surface model

env_dissimilarity

Dissimilarity between environments

plot.performs_ammi

Several types of residual plots

Multi-trait selection index

Several types of residual plots

print.ecovalence

Print an object of class ecovalence

print.corr_coef

Print an object of class corr_coef

Combines data.frames by row filling missing values

Print an object of class waasb

Plot the multi-trait genotype-ideotype distance index

Genotype by trait biplot

plot.ge_factanal

Plot the ge_factanal model

plot.ge_effects

Plot an object of class ge_effects

Plot the Smith-Hazel index

Several types of residual plots

Predict the means of a waas object

Predict method for waasb fits

Variance-covariance matrices for designed experiments

Collinearity Diagnostics

coincidence_index

Computes the coincidence index of genotype selection

Plot the multi-trait stability index

Cross-validation procedure

Split a data frame by factors

Data from an alpha lattice design

Generate significance stars from p-values

Multi-Environment Trial Analysis

Genotype analysis by fixed-effect models

Single maize trial

Genotype-Ideotype Distance Index

Tukey Honest Significant Differences

Plot the confidence interval for correlation

Additive Main effects and Multiplicative Interaction

Plot the BLUPs for genotypes

Geometric adaptability index

Plot WAASBY values for genotype ranking

Predict method for gamem fits

print.coincidence

Print an object of class coincidence

Print an object of class Fox

print.AMMI_indexes

Print an object of class AMMI_indexes

print.Annicchiarico

Print an object of class Annicchiarico

Several types of residual plots

plot.ge_cluster

Plot an object of class ge_cluster

Plot heat maps with genotype ranking

Print an object ofclass Huehn

Plot the eigenvalues

Print the partial correlation coefficients

Print an object of class ge_stats

Tidy eval helpers

Plot scores in different graphical interpretations

Utilities for handling with classes

Data for examples

Encode variables to a factor

Mantel test for a set of correlation matrices

Linear and Partial Correlation Coefficients

Mahalanobis Distance

Path coefficients with minimal multicollinearity

Predict a two-way table based on GGE model

Coerce to an object of class lpcor

Create GGE biplots

Plot an object of class ge_reg

print.colindiag

Print an object of class colindiag

print.Thennarasu

Print an object ofclass Thennarasu

print.anova_ind

Print an object of class anova_ind

print.superiority

Print an object ofclass superiority

Print an object of class sh

Print an object of class ge_reg

Weighting between stability and mean performance

Utilities for handling with NA values

print.ge_factanal

Print an object of class ge_factanal

Utilities for handling with matrices

predict.performs_ammi

Predict the means of a performs_ammi object

print.anova_joint

Print an object of class anova_joint

Objects exported from other packages

Reorder a correlation matrix

Print an object of class can_cor

print.env_dissimilarity

Print an object of class env_dissimilarity

Rescale a variable to have specified minimum and maximum values

Several types of residual plots

print.performs_ammi

Print an object of class performs_ammi

Weighted Average of Absolute Scores

Response surface model

Print an object of class Schmildt

print.path_coeff

Print an object of class path_coeff

Print an object of class Shukla

Print an object of class gamem

Weighted Average of Absolute Scores

Print an object of class mtsi

Print an object of class waas

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.waas_means

Print an object of class waas_means

Personalized theme for ggplot2-based graphics

Weighted Average of Absolute Scores

Lin e Binns' superiority index

Useful functions for computing descriptive statistics

Pseudoinverse of a square matrix

Utilities for handling with numbers and strings

utils_rows_cols

Utilities for handling with rows and columns