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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