jaccard.test.mca {jaccard}

Compute p-value using the Measure Concentration Algorithm

Description

Compute statistical significance of Jaccard/Tanimoto similarity coefficients.

Usage

jaccard.test.mca(x, y, px = NULL, py = NULL, accuracy = 1e-05,
  error.type = "average", verbose = TRUE)

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)

accuracy

an error bound on approximating a multinomial distribution

error.type

an error type on approximating a multinomial distribution ("average", "upper", "lower")

verbose

whether to print progress messages

Value

jaccard.test.mca 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.mca(x,y,accuracy = 1e-05)