perf() function returns NAs for choice.ncomp on plsda object

[Max-Bladen]

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🐞 Describe the bug:

Using the perf() function on a basic plsda object with nrepeat < 3 yields irregular results. The figure is produced fine as is most of the output components. However, upon calling the $choice.ncomp parameter, the dataframe returned contains NAs for all distances and both error rates.

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🔍 reprex results from reproducible example including sessioninfo():

library(mixOmics)
data(srbct) # extract the small round bull cell tumour data
X <- srbct$gene # use the gene expression data as the X matrix
Y <- srbct$class # use the class data as the Y matrix

initial.plsda <- plsda(X, Y, ncomp = 5)

plsda.perf <- perf(initial.plsda, progressBar = FALSE, auc = TRUE, 
                   folds = 3, nrepeat = 1)
plot(plsda.perf) # look at the output of the perf function

plsda.perf$choice.ncomp
#>         max.dist centroids.dist mahalanobis.dist
#> overall       NA             NA               NA
#> BER           NA             NA               NA

^{Created on 2022-03-07 by the reprex package (v2.0.1)}

Session info

sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#>  setting  value
#>  version  R version 4.1.2 Patched (2021-11-16 r81220)
#>  os       Windows 10 x64 (build 19042)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language (EN)
#>  collate  English_Australia.1252
#>  ctype    English_Australia.1252
#>  tz       Australia/Sydney
#>  date     2022-03-07
#>  pandoc   2.14.2 @ C:/Users/Work/AppData/Local/Pandoc/ (via rmarkdown)
#> 
#> - Packages -------------------------------------------------------------------
#>  package      * version date (UTC) lib source
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#> ------------------------------------------------------------------------------

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🤔 Expected behavior:
Despite the inability for a t.test to be performed between ncomp values with less than three repeats, for rapid exploration and experimentation with the plsda() function, there should be a work around for this.

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💡 Possible solution:
If nrepeat = 1, then just take the minimum value. If nrepeat = 2, take the minimum mean of the two repeat error rates.