View source: R/group.rankings.R
group | R Documentation |
Create an object of class "grouped_rankings"
which associates a
group index with an object of class "rankings"
. This allows the
rankings to be linked to covariates with group-specific values as the basis
for model-based recursive partitioning, see pltree
.
group(x, index, ...) as.grouped_rankings(x, ...) ## S3 method for class 'paircomp' as.grouped_rankings(x, ...) ## S3 method for class 'grouped_rankings' x[i, j, ..., drop = TRUE, as.grouped_rankings = TRUE] ## S3 method for class 'grouped_rankings' format(x, max = 2L, width = 20L, ...)
x |
a |
index |
a numeric vector of length equal to the number of rankings specifying the subject for each ranking. |
... |
additional arguments passed on to |
i |
indices specifying groups to extract, may be any data type accepted
by |
j |
indices specifying items to extract, as for |
drop |
if |
as.grouped_rankings |
if |
max |
the maximum number of rankings to format per subject. |
width |
the maximum width in number of characters to format each ranking. |
An object of class "grouped_rankings"
, which is a vector of
of group IDs with the following attributes:
rankings |
The |
index |
An index match each ranking to each group ID. |
R |
A matrix with items ordered from last to first place, for each ranking. |
S |
The rankings matrix with the ranks replaced by the size of the chosen set for free choices and zero for forced choices. |
id |
A list with elements of the adjacency matrix that are incremented by each ranking. |
pltree
# ungrouped rankings (5 rankings, 4 items) R <- as.rankings(matrix(c(1, 2, 0, 0, 0, 2, 1, 0, 0, 0, 1, 2, 2, 1, 0, 0, 0, 1, 2, 3), ncol = 4, byrow = TRUE)) length(R) R # group rankings (first three in group 1, next two in group 2) G <- group(R, c(1, 1, 1, 2, 2)) length(G) ## by default up to 2 rankings are shown per group, "..." indicates if ## there are further rankings G print(G, max = 1) ## select rankings from group 1 G[1,] ## exclude item 3 from ranking G[, -3] ## rankings from group 2, excluding item 3 ## - note group 2 becomes the first group G[2, -3] ## index underlying rankings without creating new grouped_rankings object G[2, -3, as.grouped_rankings = FALSE]
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