jaccard.test.bootstrap: Compute p-value using the bootstrap procedure

In ncchung/jaccard: Testing similarity between binary datasets using Jaccard/Tanimoto coefficients

Description

Compute statistical significance of Jaccard/Tanimoto similarity coefficients.

Usage

jaccard.test.bootstrap(x, y, px = NULL, py = NULL, verbose = TRUE,
  fix = "x", B = 1000, seed = NULL)

Arguments

x	a binary vector (e.g., fingerprint)
y	a binary vector (e.g., fingerprint)
px	probability of successes in x (optional)
py	probability of successes in y (optional)
verbose	whether to print progress messages
fix	whether to fix (i.e., not resample) x and/or y
B	a total bootstrap iteration
seed	a seed for a random number generator

Value

jaccard.test.bootstrap returns a list consisting of

statistics	centered Jaccard/Tanimoto similarity coefficient
pvalue	p-value
expectation	expectation

Examples

set.seed(1234)
x = rbinom(100,1,.5)
y = rbinom(100,1,.5)
jaccard.test.bootstrap(x,y,B=500)

ncchung/jaccard documentation built on Dec. 31, 2019, 8:20 p.m.