Multi Environment Trials Analysis
Response surface model
Schmildt's genotypic confidence index
Select helper
Stability analysis based on Wricke's model
Mahalanobis Distance
Plot the eigenvalues
Plot scores in different graphical interpretations
Plot an object of class ge_effects
Plot the ge_factanal model
Plot an object of class ge_reg
Create GGE, GT or GYT biplots
Plot the multi-trait genotype-ideotype distance index
Plot the multi-trait stability index
Plot the multi-trait stability index
Plots an object of class path_coeff
Several types of residual plots
Plot the response surface model
Print an object of class anova_joint
Print an object of class can_cor
Print an object of class coincidence
Print an object of class colindiag
Print an object of class corr_coef
Print an object of class ecovalence
Print an object of class env_dissimilarity
Print the env_stratification model
Print an object of class Fox
Print an object of class gamem
Print an object of class ge_factanal
Print an object of class ge_reg
Print an object of class ge_stats
Print an object ofclass Huehn
Print the partial correlation coefficients
Print an object of class mgidi Print a mgidi
object in two ways. By ...
Print an object of class mtmps
Print an object of class mtsi
Print an object of class path_coeff
Print an object of class performs_ammi
Print an object of class plaisted_peterson
Print an object of class Schmildt
Print an object of class sh
Print an object of class Shukla
Print an object ofclass superiority
Print an object ofclass Thennarasu
Print an object of class waas_means
Print an object of class waas
Print an object of class waasb
Objects exported from other packages
Reorder a correlation matrix
Rescale a variable to have specified minimum and maximum values
Several types of residual plots
Network plot of a correlation matrix
Cross-validation procedure
Adjusted Coefficient of Variation \loadmathjax
AMMI-based stability indexes
Alternative to dplyr::do for doing anything
Annicchiarico's genotypic confidence index
Within-environment analysis of variance
Joint analysis of variance
Arrange separate ggplots into the same graphic
Coerce to an object of class lpcor
Fast way to create bar plots
Bind cross-validation objects
Stability indexes based on a mixed-effect model
Canonical correlation analysis
Clustering analysis
Computes the coincidence index of genotype selection
Collinearity Diagnostics
Pairwise combinations of variables
Confidence interval for correlation coefficient
Linear and partial correlation coefficients
Focus on section of a correlation matrix
Visualization of a correlation matrix
Sample size planning for a desired Pearson's correlation confidence in...
Simulate genotype and genotype-environment data
Correlation between stability indexes
Generate correlated variables
Variance-covariance matrices for designed experiments
Cross-validation procedure
Cross-validation procedure
Descriptive statistics
Dissimilarity between environments
Environment stratification
Multi-trait selection index
Find possible outliers in a dataset
Details for genotype-environment trials
Fox's stability function
Genotype analysis by fixed-effect models
Geometric adaptability index
Genotype-environment analysis by mixed-effect models
Genotype analysis by mixed-effect models
Adjusted Coefficient of Variation as yield stability index
Cluster genotypes or environments
Genotype plus genotype-by-environment model
Genotype by trait biplot
Genotype-environment effects
Stability analysis and environment stratification
Genotype-environment means
Graphical analysis of genotype-vs-environment interaction
Genotype by yield*trait biplot
Huehn's stability statistics
Power Law Residuals as yield stability index \loadmathjax
Eberhart and Russell's regression model
Parametric and non-parametric stability statistics
Genotype-environment winners
Generate normal, correlated variables
Generate a covariance matrix
Get a distance matrix
Get data from a model easily
Missing value imputation
Check for common errors in multi-environment trial data
Check if a data set is balanced
Coerce to an object of class lpcor
Fast way to create line plots
Linear and Partial Correlation Coefficients
Mahalanobis distance from designed experiments
Multi-trait stability index
Two-way table to a 'long' format
Make a two-way table
Mantel test \loadmathjax
Multi-Environment Trial Analysis
Multitrait Genotype-Ideotype Distance Index
Mean performance and stability in multi-environment trials
Multi-trait mean performance and stability index
Select a set of predictors with minimal multicollinearity
Mantel test for a set of correlation matrices
Path coefficients with minimal multicollinearity
Additive Main effects and Multiplicative Interaction
Pipe operator
Stability analysis based on Plaisted and Peterson (1959)
Plot the BLUPs for genotypes
Plot the confidence interval for correlation
Plot WAASBY values for genotype ranking
Several types of residual plots
Plots an object of class can_cor
Plot an object of class clustering
Create a correlation heat map
Plot an object of class correlated_vars
Plot the RMSPD of a cross-validation procedure
Plot an object of class env_dissimilarity
Plot the env_stratification model
Multi-trait selection index
Several types of residual plots
Several types of residual plots
Plot an object of class ge_cluster
Plot the Smith-Hazel index
Several types of residual plots
Several types of residual plots
Plot heat maps with genotype ranking
Predict method for gamem fits
Print an object of class anova_ind
Predict a two-way table based on GGE model
Predict the means of a performs_ammi object
Predict the means of a waas object
Predict method for waasb fits
Print an object of class ammi_indexes
Print an object of class Annicchiarico
Selects a best subset of predictor variables.
Shukla's stability variance parameter
Smith-Hazel index
Pseudoinverse of a square matrix
Split a data frame by factors
Generate significance stars from p-values
Lin e Binns' superiority index
Personalized theme for ggplot2-based graphics
Thennarasu's stability statistics
Tidy eval helpers
Transpose a data frame
Tukey Honest Significant Differences
Encode variables to a specific format
Helper function for binding rows
Utilities for handling with classes
Utilities for data organization
Utilities for data Copy-Pasta
Utilities for handling with matrices
Utilities for handling with NA and zero values
Utilities for handling with numbers and strings
Utilities for text progress bar in the terminal
Utilities for handling with rows and columns
Random Sampling
Utilities for set operations for many sets
Useful functions for computing descriptive statistics
Set and get the Working Directory quicky
Draw Venn diagrams
Weighted Average of Absolute Scores
Weighted Average of Absolute Scores
Weighted Average of Absolute Scores
Weighting between stability and mean performance
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) <doi:10.2135/cropsci2013.04.0241>, Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, geometric adaptability index by Mohammadi & Amri (2008) <doi:10.1007/s10681-007-9600-6>, joint regression analysis by Eberhart & Russel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>, genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method, power law residuals (POLAR) statistics by Doring et al. (2015) <doi:10.1016/j.fcr.2015.08.005>, scale-adjusted coefficient of variation by Doring & Reckling (2018) <doi:10.1016/j.eja.2018.06.007>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted average of absolute scores by Olivoto et al. (2019a) <doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>. Non-parametric methods includes superiority index by Lin & Binns (1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic stability by Huehn (1990) <doi:10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) <doi:10.1007/BF00040364>. 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.
Useful links