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Returns a vector of adjusted depth-based ranks for infimal depth for functional data.
infimalRank(ID, IA, ties.method = "max")The vector of infimal depths of the curves of length n.
The vector of the infimal areas corresponding to the infimal depths from ID
of length n.
Parameter for breaking ties in infimal area index. By default max, see
rank.
A vector of length n. Low depth values mean high ranks, i.e. potential outlyingness.
If some of the infimal depths are identical, the ranking of these functions is made according to the
values of the infimal area. There, higher infimal area index means higher rank, i.e. non-centrality.
Infimal depths for functional data tend to give to many functional observations the same
value of depth. Using this function, the data whose depth is the same is ranked according
to the infimal area indicator. This indicator is provided in functions depthf.fd1 along
the value of the infimal depth.
Nagy, S., Gijbels, I. and Hlubinka, D. (2017). Depth-based recognition of shape outlying functions. Journal of Computational and Graphical Statistics, 26 (4), 883--893.
# NOT RUN {
datafA = dataf.population()$dataf[1:20]
datafB = dataf.population()$dataf[21:50]
D = depthf.fd1(datafA,datafB)
infimalRank(D$Half_ID,D$Half_IA)
ID = c(0,1,0,0,0,1,1)
IA = c(2,3,1,0,2,4,1)
infimalRank(ID,IA)
# }
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