Function to view all adjustment quality statistics of trained RNA repeats

Question

I’m training several Rnas with 100 reps each. I need a function that shows all adjustment quality statistics for all repeats.

# RNA 1 
set.seed(5)
RNA1 <- neuralnet(paste("Ht_norm ~ ", Quant.var), base_treinamento, hidden = 2,
          act.fct = 'logistic' ,algorithm = "rprop+", err.fct = "sse",
          linear.output = FALSE, rep = 100)
plot(RNA1, rep = 1)

where Rep = number of repetitions.

I can observe the adjustment quality statistics one repetition at a time, but it is impossible for me to write 100 lines of code to observe all the adjustment quality statistics for the 100 repetitions. Below the function I created to view such adjustment quality statistics.

# Stat Model Function 
StatModel <- function(obs, est, plotR = TRUE, xlim = NULL, ylim = NULL, col = "black", xlab = "Observed", ylab = "Predicted", main = NULL) {
  rmse <- sqrt(sum((obs-est)^2)/length(obs)) # Root mean square error
  bias <- mean(obs-est) # bias
  rmseR <- 100*sqrt(sum((obs-est)^2)/length(obs))/mean(obs)
  biasR <- 100*mean(obs-est)/mean(obs)
  MAE <- sum((obs-est)^2)/length(obs) # Mean absolute error
  PMRE <- sum(sqrt(((obs-est)/obs)^2)/length(obs))*100 # percent mean relative error. (PMRE)
}

To observe one at a time, I use the sequence:

base_validacao$Ht_RNA1_Est <- predict(RNA1, rep = 1, base_validacao)
StatModel(base_validacao$Ht_norm, base_validacao$Ht_RNA1_Est,
  xlim = c(0,1), ylim = c(0,1), main = "RNA1-Treino" )

Again, where rep = repetition number