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metan (version 1.6.0)

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) , 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

3,776

Version

1.6.0

License

GPL-3

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Repository

https://github.com/TiagoOlivoto/metan

Maintainer

Tiago Olivoto

Last Published

May 21st, 2020

Functions in metan (1.6.0)

Resende_indexes

Stability indexes based on a mixed-effect model

Thennarasu's stability statistics

Fast way to create bar plots

Bind cross-validation objects

Arrange multiple ggplot2 graphics in a single image window

Smith-Hazel index

Annicchiarico's genotypic confidence index

Computes Pearson's correlation matrix with p-values

AMMI-based stability indexes

Visualization of a correlation matrix

Coerce to an object of class lpcor

Pairwise combinations of variables

Confidence interval for correlation coefficient

Fox's stability function

coincidence_index

Computes the coincidence index of genotype selection

Within-environment analysis of variance

Cross-validation procedure

Single maize trial

Shukla's stability variance parameter

Variance-covariance matrices for designed experiments

Joint analysis of variance

Huehn's stability statistics

Data from an alpha lattice design

Canonical correlation analysis

Cluster genotypes or environments

Multi-environment trial of maize

Genotype plus genotype-by-environment model

Collinearity Diagnostics

Details for genotype-environment trials

Cross-validation procedure

Multi-environment trial of oat

Clustering analysis

Genotype by trait biplot

Find possible outliers in a dataset

Multi-trait selection index

Geometric adaptability index

Genotype analysis by fixed-effect models

Multi-Environment Trial Analysis

Genotype-environment effects

Stability analysis and environment stratification

Genotype-Ideotype Distance Index

Correlation between stability indexes

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

Genotype-environment winners

Cross-validation procedure

Make a two-way table

Statistics for genotype-vs-environment interaction

Additive Main effects and Multiplicative Interaction

Eberhart and Russell's regression model

Data for examples

Stability analysis based on Wricke's model

Get data from a model easily

Mahalanobis distance from designed experiments

Descriptive statistics

plot.anova_joint

Several types of residual plots

env_dissimilarity

Dissimilarity between environments

Multi-trait stability index

Two-way table to a 'long' format

non_collinear_vars

Select a set of predictors with minimal multicollinearity

Alternative to dplyr::do for doing anything

Plots an object of class can_cor

Several types of residual plots

Genotype-environment means

Genotype analysis by mixed-effect models

Genotype-environment analysis by mixed-effect models

Several types of residual plots

Plot heat maps with genotype ranking

Graphical analysis of genotype-vs-environment interaction

plot.ge_cluster

Plot an object of class ge_cluster

Data for examples

Coerce to an object of class lpcor

impute_missing_val

Missing value imputation

Check for common errors in multi-environment trial data

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

is_balanced_trial

Check if a data set is balanced

Plot the eigenvalues

Mantel test for a set of correlation matrices

plot.env_dissimilarity

Plot an object of class env_dissimilarity

Linear and Partial Correlation Coefficients

Mahalanobis Distance

Fast way to create line plots

Multi-trait selection index

Several types of residual plots

plot.performs_ammi

Several types of residual plots

Plot WAASBY values for genotype ranking

Plot the response surface model

Predict method for gamem fits

Create a correlation heat map

plot.clustering

Plot an object of class clustering

plot.ge_effects

Plot an object of class ge_effects

Print an object of class Schmildt

Predict the means of a waas object

Plot the BLUPs for genotypes

Plot the confidence interval for correlation

Predict method for waasb fits

print.AMMI_indexes

Print an object of class AMMI_indexes

Print an object of class can_cor

plot.ge_factanal

Plot the ge_factanal model

Plot the multi-trait genotype-ideotype distance index

print.anova_joint

Print an object of class anova_joint

print.ge_factanal

Print an object of class ge_factanal

Plot the multi-trait stability index

print.Annicchiarico

Print an object of class Annicchiarico

Print an object of class ge_reg

Plot scores in different graphical interpretations

print.path_coeff

Print an object of class path_coeff

Pseudoinverse of a square matrix

Utilities for handling with matrices

Response surface model

Utilities for handling with NA values

print.performs_ammi

Print an object of class performs_ammi

Path coefficients with minimal multicollinearity

print.coincidence

Print an object of class coincidence

print.Thennarasu

Print an object ofclass Thennarasu

Tidy eval helpers

print.colindiag

Print an object of class colindiag

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 mtsi

Encode variables to a factor

Print an object of class waasb

print.anova_ind

Print an object of class anova_ind

print.corr_coef

Print an object of class corr_coef

print.ecovalence

Print an object of class ecovalence

Personalized theme for ggplot2-based graphics

Lin e Binns' superiority index

Combines data.frames by row filling missing values

Utilities for handling with numbers and strings

Print an object of class Shukla

Plot an object of class ge_reg

utils_rows_cols

Utilities for handling with rows and columns

Objects exported from other packages

Reorder a correlation matrix

print.superiority

Print an object ofclass superiority

Print an object of class ge_stats

Print an object of class sh

Print the partial correlation coefficients

Create GGE biplots

Plot the Smith-Hazel index

Tukey Honest Significant Differences

Several types of residual plots

Rescale a variable to have specified minimum and maximum values

Utilities for handling with classes

Weighted Average of Absolute Scores

Several types of residual plots

Weighting between stability and mean performance

Weighted Average of Absolute Scores

predict.performs_ammi

Predict the means of a performs_ammi object

Predict a two-way table based on GGE model

Print an object ofclass Huehn

Print an object of class Fox

print.env_dissimilarity

Print an object of class env_dissimilarity

Print an object of class gamem

Print an object of class waas

print.waas_means

Print an object of class waas_means

Split a data frame by factors

Useful functions for computing descriptive statistics

Generate significance stars from p-values

Weighted Average of Absolute Scores

Schmildt's genotypic confidence index