Description Usage Arguments Value References Examples
Given a partial order (arguments profiles
for the set of profiles and/or
zeta
for the incidence matrix) a selected threshold
,
the function returns an object of S3 class parsec
, a list of objects described in
Value section. In particular the function returns the identification function,
different gap measures and, if required, an inequality measure. Moreover the list
contains starting data informations and computational details.
Results are obtained by uniform sampling of the linear extensions of the poset, by using the Bubley Dyer (1999) algorithm.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | 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,
inequality = TRUE
)
|
profiles |
an object of S3 class |
threshold |
a vector to select profiles as threshold. It can be a vector of indexes (numeric), a vector of profiles names (character) or a boolean vector as long as the number of profiles. |
error |
the error of approximation of the frequencies to the uniformity to sample the linear extensions. |
zeta |
the incidence matrix of the poset. An object of S3 class |
weights |
weights to assign to profiles. If the argument |
distances |
matrix of distances between profiles. The matrix has to be square, the dimensions have to be equal to the number of profiles and complete. Even if the matrix is complete, the distance between two profiles profiles is considered only if one profile covers the other. |
linext |
the initializing linear extension, by default generated by |
nit |
Number Of Iterations, by default evaluated from a formula of Karzanov and Khachiyan
from the number of profiles and the argument |
maxint |
Maximum integer. By default the maximum integer obtainable in a 32bit system.
This argument is used to groups the iterations and run different times the compiled
C library, in order to avoid memory indexing problems. Therefore the user can
set a lower value to |
inequality |
differently from the other measures, the complexity of the algorithm used to evaluate
inequality is more than linear, therefore, the user can choose if evaluate
inequality with this boolean parameter (by default |
profiles |
an object of S3 class |
number_of_profiles |
number of profiles. |
number_of_variables |
number of variables. |
incidence |
S3 class |
cover |
S3 class |
threshold |
boolean vector indicating whether a profile belongs to the threshold. |
number_of_iterations |
number of iterations performed by the Bubley Dyer algorithm. |
rank_relative_frequencies |
matrix that by rows reports the relative frequencies distribution of the ranks for each profile. |
threshold_relative_frequencies |
vector that reports the relative frequency of the times a profile is used as threshold in the sampled linear extensions. This result is useful for posterior valuation of the poset threshold. |
profiles_weights |
vector of weights assigned to each profile. |
edges_weights |
matrix of distances between profiles, used to evaluate the measures of gap. |
identification_function |
vector that reports the relative frequency of times that a profile is equal or lower than the threshold of the linear extension. |
point_absolute_poverty_gap |
vector that reports the average absolute distance from the first profile greater than the threshold of the linear extension. This gap is set equal to 0 when the profile is greater than the threshold in the linear extension. |
point_relative_poverty_gap |
the previous absolute distance is divided by its maximum possible value, that is the absolute distance of the first profile greater than the threshold from the minimal element in the linear extension. |
point_absolute_wealth_gap |
vector that reports the average absolute distance from the threshold of the linear extension. This gap is set equal to 0 when the profile is lower than or equal to the threshold in the linear extension. |
point_relative_wealth_gap |
the previous absolute distance is divided by its maximum possible value, that is the absolute distance of the threshold from the maximal element in the linear extension. |
poverty_gap |
mean over the profiles of |
wealth_gap |
mean over the profiles of |
inequality |
when the argument |
Bubley R., Dyer M. (1999), Faster random generation of linear extensions, Discrete Math., 201, 81-88.
Fattore M., Arcagni A. (2013), Measuring multidimensional polarization with ordinal data, SIS 2013 Statistical Conference, BES-M3.1 - The BES and the challenges of constructing composite indicators dealing with equity and sustainability
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