sracppfull: Compute the sequential rank agreement between k ranked lists

In SuperRanker: Sequential Rank Agreement

Compute the sequential rank agreement between k ranked lists

Description

Computes the sequential rank agreement (number of items present in all k lists divided by the current rank) for each rank in the k lists

Usage

sracppfull(rankMat, type = 0L, epsilon = as.numeric(c(0)))

Arguments

rankMat	A matrix with k columns corresponding to the k ranked lists. Elements of each column are integers between 1 and the length of the lists
type	The type of distance measure to use: 0 (the default) is the variance while 1 is MAD (mean absolute deviation)
epsilon	A non-negative numeric vector that contains the minimum limit in proportion of lists that must show the item. Defaults to 0. If a single number is provided then the value will be recycles to the number of items.

Value

A vector of the same length as the rows in rankMat containing the sequential rank agreement between the lists for each depth (squared for type=0)

Author(s)

Claus Ekstrøm <[e-mail]>

SuperRanker documentation built on Aug. 28, 2023, 1:08 a.m.