WD

expr min lq mean median uq max neval postmean 102.7708 113.6098 134.5917 117.8156 130.2786 294.1863 100 postsd 225.2152 238.8804 277.1865 252.2738 325.9447 420.9524 100

I was profiling fsusie, which uses these two functions a lot at every loop (2^S x number of covariates) so I just thought that could be place to gain speed...

I have run some benchmark comparison and ebnm is actually 1.5 slower than ash when computing posterior quantities. I see the same pattern (posterior sd computation being slower than posterior...