ge_factanal: Stability analysis and environment stratification

Description

This function computes the stability analysis and environmental stratification using factor analysis as proposed by Murakami and Cruz (2004).

Usage

ge_factanal(.data, env, gen, rep, resp, mineval = 1, verbose = TRUE)

Arguments

.data

The dataset containing the columns related to Environments, Genotypes, replication/block and response variable(s)

env

The name of the column that contains the levels of the environments.

gen

The name of the column that contains the levels of the genotypes.

rep

The name of the column that contains the levels of the replications/blocks

resp

The response variable(s). To analyze multiple variables in a single procedure use, for example, resp = c(var1, var2, var3).

mineval

The minimum value so that an eigenvector is retained in the factor analysis.

verbose

Logical argument. If verbose = FALSE the code will run silently.

Value

An object of class ge_factanal with the following items:

data

The data used to compute the factor analysis.

cormat

The correlation matrix among the environments.

PCA

The eigenvalues and explained variance.

The factor analysis.

env_strat

The environmental stratification.

KMO

The result for the Kaiser-Meyer-Olkin test.

MSA

The measure of sampling adequacy for individual variable.

communalities

The communalities.

communalities.mean

The communalities' mean.

initial.loadings

The initial loadings.

finish.loadings

The final loadings after varimax rotation.

canonical.loadings

The canonical loadings.

scores.gen

The scores for genotypes for the first and second factors.

References

Murakami, D.M.D., and C.D.C. Cruz. 2004. Proposal of methodologies for environment stratification and analysis of genotype adaptability. Crop Breed. Appl. Biotechnol. 4:7-11.

Examples

Run this code

# NOT RUN {
library(metan)
model = ge_factanal(data_ge2,
                    env = ENV,
                    gen = GEN,
                    rep = REP,
                    resp = PH)

# }

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