kendallMLists: KendallMLists
In TopKLists: Inference, Aggregation and Visualization for Top-K Ranked Lists

KendallMLists

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 `p=0.5` for a "neutral approach".)
`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.

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)

TopKLists documentation built on Sept. 1, 2022, 5:10 p.m.