Print the ge_factanal object in two ways. By default, the results are
shown in the R console. The results can also be exported to the directory.
Usage
# S3 method for ge_factanal
print(x, export = FALSE, file.name = NULL, digits = 4, ...)Arguments
- x
An object of class
ge_factanal.- export
A logical argument. If
TRUE, a *.txt file is exported to the working directory- file.name
The name of the file if
export = TRUE- digits
The significant digits to be shown.
- ...
Options used by the tibble package to format the output. See
tibble::print()for more details.
Author
Tiago Olivoto tiagoolivoto@gmail.com
Examples
# \donttest{
model <- ge_factanal(data_ge2,
env = ENV,
gen = GEN,
rep = REP,
resp = PH
)
print(model)
#> Variable PH
#> ------------------------------------------------------------------------------------
#> Correlation matrix among environments
#> ------------------------------------------------------------------------------------
#> # A tibble: 4 × 5
#> ENV A1 A2 A3 A4
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 A1 1 0.3919 -0.4723 -0.4983
#> 2 A2 0.3919 1 -0.2203 0.2722
#> 3 A3 -0.4723 -0.2203 1 0.3238
#> 4 A4 -0.4983 0.2722 0.3238 1
#> ------------------------------------------------------------------------------------
#> Eigenvalues and explained variance
#> ------------------------------------------------------------------------------------
#> # A tibble: 4 × 4
#> PCA Eigenvalues Variance Cumul_var
#> <chr> <dbl> <dbl> <dbl>
#> 1 PC1 1.926 48.15 48.15
#> 2 PC2 1.263 31.58 79.74
#> 3 PC3 0.5928 14.82 94.56
#> 4 PC4 0.2178 5.444 100
#> ------------------------------------------------------------------------------------
#> Initial loadings
#> ------------------------------------------------------------------------------------
#> # A tibble: 4 × 3
#> Env FA1 FA2
#> <chr> <dbl> <dbl>
#> 1 A1 -0.8912 0.08731
#> 2 A2 -0.3718 0.8816
#> 3 A3 0.7660 -0.04547
#> 4 A4 0.6380 0.6902
#> ------------------------------------------------------------------------------------
#> Loadings after varimax rotation and commonalities
#> ------------------------------------------------------------------------------------
#> # A tibble: 4 × 5
#> Env FA1 FA2 Communality Uniquenesses
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 A1 -0.8763 0.1839 0.8018 0.1982
#> 2 A2 -0.2735 0.9169 0.9154 0.08461
#> 3 A3 0.7564 -0.1287 0.5888 0.4112
#> 4 A4 0.7095 0.6166 0.8835 0.1165
#> ------------------------------------------------------------------------------------
#> Environmental stratification based on factor analysis
#> ------------------------------------------------------------------------------------
#> # A tibble: 4 × 6
#> Env Factor Mean Min Max CV
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 A1 FA1 2.793 2.692 2.935 2.810
#> 2 A3 FA1 2.167 2.028 2.599 7.724
#> 3 A4 FA1 2.518 2.305 2.638 3.655
#> 4 A2 FA2 2.462 1.959 2.947 16.20
#> ------------------------------------------------------------------------------------
#> Mean = mean; Min = minimum; Max = maximum; CV = coefficient of variation (%)
#> ------------------------------------------------------------------------------------
#>
#>
#>
# }