env_stratification {metan} | R Documentation |
Environment stratification
Description
Computes environment stratification based on factor analysis.
Usage
env_stratification(
.data,
env,
gen,
resp,
use = "complete.obs",
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. |
resp |
The response variable(s). To analyze multiple variables in a
single procedure use, for example, |
use |
The method for computing covariances in the presence of missing
values. Defaults to |
mineval |
The minimum value so that an eigenvector is retained in the factor analysis. |
verbose |
Logical argument. If |
Value
An object of class env_stratification
which is a list with one
element per analyzed trait. For each trait, the following values are given.
-
data
The genotype-environment means. -
cormat
: The correlation matrix among the environments. -
PCA
: The eigenvalues and explained variance. -
FA
: The factor analysis. -
env_strat
: The environmental stratification. -
mega_env_code
: The environments within each mega-environment. -
mega_env_stat
: The statistics for each mega-environment. -
KMO
: The result for the Kaiser-Meyer-Olkin test. -
MSA
: The measure of sampling adequacy for individual variable. -
communalities_mean
: The communalities' mean. -
initial_loadings
: The initial loadings.
Author(s)
Tiago Olivoto, tiagoolivoto@gmail.com
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.
See Also
Examples
library(metan)
model <-
env_stratification(data_ge,
env = ENV,
gen = GEN,
resp = everything())
gmd(model)