Factor Analytic Summary

## Usage

```
fa_summary(
model = NULL,
trial = "trial",
genotype = "genotype",
BLUEs_trial = NULL,
mult_fa1 = -1,
mult_fa2 = 1,
filter_score = 1.5,
k_biplot = 1,
size_label_var = 2,
alpha_label_var = 0.2,
size_label_ind = 2,
alpha_label_ind = 0.8,
size_arrow = 0.2,
alpha_arrow = 0.2,
base_size = 12
)
```

## Arguments

- model
Factor Analytic Model (ASReml object)

- trial
A character string indicating the column in data that contains trials.

- genotype
A character string indicating the column in data that contains genotypes.

- BLUEs_trial
A data.frame containing BLUEs for each trial.

- mult_fa1
A constant to multiply the first loading. Must be 1 or -1. (-1 by default)

- mult_fa2
A constant to multiply the second loading. Must be 1 or -1. (1 by default)

- filter_score
A numeric value to filter genotypes by the distance from the origin.

- k_biplot
A numeric value to multiply the scores in the biplot.

- size_label_var
A numeric value to define the label size for the variables.

- alpha_label_var
A numeric value between (0,1) to define the label for the variables.

- size_label_ind
A numeric value to define the label size for the individuals.

- alpha_label_ind
A numeric value between (0,1) to define the label for the individuals.

- size_arrow
A numeric value to define the arrow size.

- alpha_arrow
A numeric value between (0,1) to define the arrow.

- base_size
A numeric value to define the base size.

## Value

An object with a list of:

- loadings
A data.frame containing the first and second loading for each trial.

- loading_star
A data.frame containing the first and second loading rotated for each trial.

- Gvar
A matrix of the estimated variance-covariance between trials.

- Cmat
A matrix of the correlation between trials.

- summary_loading
A data.frame containing a summary of the loadings.

- paf_site
A data.frame containing the percentage of variance explained for each component and for each trial.

- var_tot
A numeric value of the total variance.

- scores
A data.frame containing the scores for each genotype.

- plots
A list with different plots. Includes a plot for the loadings, biplot, biplot_scaled and loadings_c.

## Examples

```
if (FALSE) {
library(agridat)
library(agriutilities)
data(besag.met)
dat <- besag.met
results <- check_design_met(
data = dat,
genotype = "gen",
trial = "county",
traits = c("yield"),
rep = "rep",
block = "block",
col = "col",
row = "row"
)
out <- single_trial_analysis(results, progress = FALSE)
met_results <- met_analysis(out, vcov = "fa2", progress = FALSE)
pp <- met_results$trial_effects
model <- met_results$met_models$yield
fa_summary(
model = model,
trial = "trial",
genotype = "genotype",
BLUEs_trial = pp,
mult_fa1 = -1,
mult_fa2 = -1,
filter_score = 1,
k_biplot = 10,
size_label_var = 3,
alpha_label_var = 0.5,
size_label_ind = 3,
alpha_label_ind = 0.8,
size_arrow = 0.2,
alpha_arrow = 0.1
)
}
```