profiles
and/or
zeta
) and a selected threshold
,
the function returns an object of S3 class parsec
.
In particular, the function returns the identification function and
different severity measures, computed by uniform sampling of the linear extensions of the poset, through a C implementation of the Bubley - Dyer (1999) algorithm.evaluation(
profiles = NULL,
threshold,
error = 10^(-3),
zeta = getzeta(profiles),
weights = {
if (!is.null(profiles))
profiles$freq
else rep(1, nrow(zeta))
},
distances = {
n <- nrow(zeta)
matrix(1, n, n) - diag(1, n)
},
linext = lingen(zeta),
nit = floor({
n <- nrow(zeta)
n^5 * log(n) + n^4 * log(error^(-1))
}),
maxint = 2^31 - 1)
wprof
.incidence
.
By default, extracted from profiles
and the order of variable modalities.profiles
is not NULL
,
weights are by default set equal to profile frequencies, otherwise they are
set equal to 1.lingen(zeta)
. Alternatively, it can be provided by
the user through a vector of profile ranks.error
(see Bubley and Dyer, 1999).maxint
iwprof
reporting poset profiles
and their associated frequencies (number of statistical units in each profile).incidence
, incidence matrix of the poset.cover
, cover matrix of the poset.profiles <- var2prof(varlen = c(3, 2, 4))
threshold <- c("311", "112")
res <- evaluation(profiles, threshold, maxint = 10^5)
summary(res)
plot(res)
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