KendallMLists {TopKLists} | R Documentation |
KendallMLists
Description
Compute Kendall's tau criterion
Usage
KendallMLists(input, space = NULL, aggregate, p = 0.5, w = NULL)
Arguments
input |
A list with each element being a top-k list to be aggregated; the top-k lists can be of variable lengths |
space |
A list with each element being the underlying space from which the corresponding top-k list is derived |
aggregate |
The aggregate list (result) from any of the three classes of algorithms |
p |
A parameter between 0 and 1 for setting the distance of a pair of elements between two lists,
if at least one of the elements is not in the underlying space of one
of the list or if both elements belong to one list but neither belongs
to the other list. (We recommend using |
w |
Weight vector assigning a weight to each list |
Value
Kendall's distance
Author(s)
Shili Lin <shili@stat.osu.edu>
References
Lin, S., Ding, J. (2009) Integration of ranked lists via Cross Entropy Monte Carlo with applications to mRNA and microRNA studies. Biometrics 65, 9-18.
Lin, S. (2010) Space oriented rank-based data integration. Statistical Applications in Genetics and Molecular Biology 9, Article 20.
See Also
Examples
data(TopKSpaceSampleInput)
bb1=Borda(input,space)
w= c(2/(30 * (30 - 1)), 2/(25 * (25 - 1)), 2/(20 * (20 -+ 1)))
kc.ARM=KendallMLists(input, space, bb1[[1]][, 1], p = 0.5, w = w)