Suppose you have an EEG dataset where every column is an electrode E1....E129.
First, you want to compute the spatial standard deviation GFP. How would you rewrite rowSD using dplyr rowwise? Next you want to normalize each electrode by dividing it with GFP. What goes into the mutate_all? Thanks!

I'm not actually that familiar with rowwise, but here is one way to do it by pivot_longer(), doing your calculations, and then pivot_wider() to get back to the same original shape.

The reason I asked is that RFunctionSN isn't a package, as such, just a collection of functions, which makes them hard to track down.

For an N x 19 data frame, rowwise operations become extremely inefficient as N increases. Converted to a matrix object, applying a function to rows is much faster and dividing all terms in a matrix also. Converting back to a tibble is possible with enframe, although you'll probably need to add back the original colnames