Specifying min eigen value in factor analysis call in R

Question

This is a statistics question--

In STATA, you can specify the minimum eigen value so that the optimal number of factors are chosen.

. forvalues i=1/11{
  2.         unab vars: `vv`i''
  3.         di _n(3)"################## vars: `vars' ##################"
  4.         factor `vv`i'',pcf mineigen(1)
  5.         rotate
  6.         alpha `vv`i''
  7.   }

Both factanal() and psych::principal() require the programmer to specify the exact number of factors in the initial call.

for example:

 fit <- factanal(mydata, 3, rotation="varimax")

I know that I can run some further exploration to find the ideal number:

https://www.statmethods.net/advstats/factor.html
    # Determine Number of Factors to Extract
    library(nFactors)
    ev <- eigen(cor(mydata)) # get eigenvalues
    ap <- parallel(subject=nrow(mydata),var=ncol(mydata),
      rep=100,cent=.05)
    nS <- nScree(x=ev$values, aparallel=ap$eigen$qevpea)
    plotnScree(nS) 

I would like R to decide on the factors to extract, without having to do any exploratory work. Is this possible in R?