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metan (version 1.2.1)

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

3,776

Version

1.2.1

License

GPL-3

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Repository

https://github.com/TiagoOlivoto/metan

Maintainer

Tiago Olivoto

Last Published

January 14th, 2020

Functions in metan (1.2.1)

Thennarasu's stability statistics

Fox's stability function

Collinearity Diagnostics

Cross-validation procedure

Variance-covariance matrices for designed experiments

Huehn's stability statistics

Arrange multiple ggplot2 graphics in a single image window

Clustering analysis

Cross-validation procedure

Joint analysis of variance

Cross-validation procedure

AMMI-based stability indexes

Descriptive statistics from long to wide

Visualization of a correlation matrix

Shukla's stability variance parameter

Confidence interval for correlation coefficient

Pairwise combinations of variables

Descriptive statistics

Computes Pearson's correlation matrix with p-values

Bind cross-validation objects

Canonical correlation analysis

Multi-environment trial of maize

Stability analysis and environment stratification

Linear and Partial Correlation Coefficients

Mantel test for a set of correlation matrices

is.split_factors

Check if an object is of class split_factors

Genotype-environment effects

Multi-environment trial of oat

Multi-trait stability index

Annicchiarico's genotypic confidence index

Multi-trait selection index

plot.cvalidation

Plot the RMSPD of a cross-validation procedure

Single maize trial

as.split_factors

Coerce to an object of class split_factors

Geometric adaptability index

Coerce to an object of class lpcor

Data from an alpha lattice design

Correlation between stability indexes

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

Genotype-environment means

Graphical analysis of genotype-vs-environment interaction

plot.env_dissimilarity

Plot an object of class env_dissimilarity

Genotype analysis by mixed-effect models

Eberhart and Russell's regression model

Statistics for genotype-vs-environment interaction

Genotype plus genotype-by-environment model

Find possible outliers in a dataset

Several types of residual plots

Plot the BLUPs for genotypes

Plot heat maps with genotype ranking

Cluster genotypes or environments

Make a two-way table

Make a symmetric matrix on a triangular matrix

plot.clustering

Plot an object of class clustering

Create a correlation heat map

plot.ge_effects

Plot an object of class ge_effects

Predict a two-way table based on GGE model

plot.ge_factanal

Plot the ge_factanal model

predict.performs_ammi

Predict the means of a performs_ammi object

Stability analysis based on Wricke's model

Details for genotype-environment trials

Print an object of class Schmildt

env_dissimilarity

Dissimilarity between environments

Genotype-environment winners

Mahalanobis Distance

Data for examples

Multi-trait selection index

Mahalanobis distance from designed experiments

Make an upper triangular matrix

plot.ge_cluster

Plot an object of class ge_cluster

Get data from a model easily

Plot the confidence interval for correlation

Plot an object of class ge_reg

Make a lower triangular matrix

Two-way table to a 'long' format

print.corr_coef

Print an object of class corr_coef

Print an object of class can_cor

Check for common erros in multi-environment trial data

Create GGE biplots

Plot scores in different graphical interpretations

Data for examples

Print an object of class Shukla

Path coefficients with minimal multicollinearity

Means by one or more factors

Multi-Environment Trial Analysis

Additive Main effects and Multiplicative Interaction

Coerce to an object of class lpcor

print.superiority

Print an object ofclass superiority

print.performs_ammi

Print an object of class performs_ammi

Print an object of class waasb

Plots an object of class can_cor

Plot the multi-trait stability index

print.Annicchiarico

Print an object of class Annicchiarico

Plot WAASBY values for genotype ranking

Plot the eigenvalues

Predict the means of a waas object

Print an object of class ge_reg

Objects exported from other packages

print.AMMI_indexes

Print an object of class AMMI_indexes

plot.performs_ammi

Several types of residual plots

Fast way to create a bar plot

Print an object of class ge_stats

Print an object of class gamem

remove_na_values

Remove NA values

Weighted Average of Absolute Scores

Weighted Average of Absolute Scores

Combines data.frames by row filling missing values

Personalized theme for ggplot2-based graphics

Lin e Binns' superiority index

Print an object of class Fox

print.path_coeff

Print an object of class path_coeff

Print an object of class mtsi

Standard Error of the Mean

Response surface model

print.ge_factanal

Print an object of class ge_factanal

Pseudoinverse of a square matrix

Several types of residual plots

Plot the response surface model

Split a data frame by factors

Weighted Average of Absolute Scores

Fast way to create a line plot

Fast way to create a line plot

print.anova_ind

Print an object of class anova_ind

print.ecovalence

Print an object of class ecovalence

print.anova_joint

Print an object of class anova_joint

Print an object of class waas

Utilities for handling with numbers and strings

print.waas_means

Print an object of class waas_means

utils_rows_cols

Utilities for handling with rows and columns

Weighting between stability and mean performance

print.env_dissimilarity

Print an object of class env_dissimilarity

Reorder a correlation matrix

Tidy eval helpers

Rescale a variable to have specified minimum and maximum values

Encode variables to a factor

Schmildt's genotypic confidence index

Resende_indexes

Stability indexes based on a mixed-effect model

Within-environment analysis of variance