indpFunc {BiCausality}

indpFunc function

Description

This function computes the degree of dependency between variables. Let i and j be variables, if they are independent, then |p(i,j) -p(i)*p(j)| should be zero. Given the samples in the n by d matrix mat where n is a number of samples and d is a number of dimensions, an aligned list of transactions D is computed by D<-VecAlignment(mat).

Usage

indpFunc(D, i, j, z = c())

Arguments

D

is an aligned list of transactions that was converted from mat.

i

is an ith dimension in mat.

j

is an jth dimension in mat.

z

is a conditioning d-dimensional vector on D. Given k non-negative-bit positions of z, all k bit positions of samples in the subset of D must have similar values with these bits.

Value

This function returns the degree of dependency between variables: zero implies both variables are independent, and non-zero value implies the degree of dependency (higher implies more dependent degree).

Examples

indpFunc(D,i=1,j=2)