| partial_forder | R Documentation | 
If the functional data doesn't comfortably fit in memory it is possible to
compute functional ordering by splitting the domain of the data (voxels in
a brain image), using partial_forder on each part and finally
combining the results with combine_forder.
partial_forder(
  curve_set,
  measure = c("erl", "rank", "cont", "area"),
  alternative = c("two.sided", "less", "greater")
)
combine_forder(ls)
curve_set | 
 A   | 
measure | 
 The measure to use to order the functions from the most extreme to the least extreme one. Must be one of the following: 'rank', 'erl', 'cont', 'area', 'max', 'int', 'int2'. Default is 'erl'.  | 
alternative | 
 A character string specifying the alternative hypothesis.
Must be one of the following: "two.sided" (default), "less" or "greater".
The last two options only available for types   | 
ls | 
 List of objects returned by partial_forder  | 
See forder
forder
data("abide_9002_23")
res <- lapply(list(1:100, 101:200, 201:261), function(part) {
  set.seed(123) # When using partial_forder, all parts must use the same seed.
  fset <- frank.flm(nsim=99, formula.full = Y ~ Group + Sex + Age,
                  formula.reduced = Y ~ Group + Sex,
                  curve_sets = list(Y = abide_9002_23$curve_set[part,]),
                  factors = abide_9002_23$factors, savefuns = "return")
  partial_forder(fset, measure="erl")
})
combine_forder(res)
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