As Frank Harrell notes in this answer:
You need modifications to the bootstrap (.632, .632+) only because the original research used a discontinuous improper scoring rule (proportion classified correctly). For other accuracy scores the ordinary optimism bootstrap tends to work fine.
Also, as discussed on this page, use of .632-type rules doesn't strictly follow a fundamental property of bootstrapping.
So I suppose that you could compute a .632+ score for other purposes, but there might not be much point. I suspect that accounts for any paucity of functions in R with respect to .632+ estimates.