test_sra: Compute a Kolmogorov-Smirnoff-like test for Smooth quantiles...

In SuperRanker: Sequential Rank Agreement

Compute a Kolmogorov-Smirnoff-like test for Smooth quantiles of a matrix of sequential rank agreements

Description

Compute a Kolmogorov-Smirnoff-like test for Smooth quantiles of a matrix of sequential rank agreements

Usage

test_sra(object, nullobject, weights = 1)

Arguments

object	An object created with sra.
nullobject	An object created with random_list_sra.
weights	Either a single value or a vector of the same length as the number of item with the weight that should be given to specific depths.

Value

A single value corresponding to the p-value

Author(s)

Claus Ekstrøm <[e-mail]>

Examples

# setting with 3 lists
mlist <- matrix(cbind(1:8,c(1,2,3,5,6,7,4,8),c(1,5,3,4,2,8,7,6)),ncol=3)
# compute sequential rank agreements
x=sra(mlist)
# compute rank agreement of 5 random permutations
null=random_list_sra(mlist,n=15)
# now extract point-wise quantiles according to confidence level
test_sra(x,null)
# compare to when we use the result of the first permutation run
test_sra(null[,1],null[,-1])

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