View source: R/tree-functions.R
V.star | R Documentation |
Computes the post hoc upper bound V^*(S)
on the number of false positives in a
given selection set S
of hypotheses, using a reference family (R_k, \zeta_k)
that possess the forest structure
(see Reference).
V.star(S, C, ZL, leaf_list)
S |
An integer vector with the indices of the hypotheses of the selection set. Does not need to be ordered. |
C |
A list of list representing the forest structure. Each list of |
ZL |
A list of integer vectors representing the upper bound |
leaf_list |
A list of vectors. Each vector is an integer array. The i-th vector contains the indices
of the hypotheses in the i-th atom. Atoms form a partition of the set of hypotheses indices :
there cannot be overlap, and each index has to be inside one of the atoms. It is really important, for all functions
using |
For V.star
, the forest structure doesn't need to be complete. That is,
in C
, some trivial intervals c(i,i)
corresponding to regions that are atoms may be missing.
An integer value, the post hoc upper bound V^*(S)
.
Durand, G., Blanchard, G., Neuvial, P., & Roquain, E. (2020). Post hoc false positive control for structured hypotheses. Scandinavian Journal of Statistics, 47(4), 1114-1148.
m <- 20
C <- list(
list(c(2, 5), c(8, 15), c(16, 19)),
list(c(3, 5), c(8, 10), c(12, 15), c(16, 16), c(17, 19)),
list(c(4, 5), c(8, 9), c(10, 10), c(12, 12), c(13, 15), c(17, 17), c(18, 19)),
list(c(8, 8), c(9, 9), c(13, 13), c(14, 15), c(18, 18), c(19, 19))
)
ZL <- list(
c(4, 8, 4),
c(3, 3, 4, 1, 3),
c(2, 2, 1, 1, 2, 1, 2),
c(1, 1, 1, 2, 1, 1)
)
leaf_list <- as.list(1:m)
V.star(1, C, ZL, leaf_list)
V.star(1:5, C, ZL, leaf_list)
V.star(13:15, C, ZL, leaf_list)
V.star(1:m, C, ZL, leaf_list)
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