c_association {stops}R Documentation

c-association calculates the c-association based on the maximal information coefficient We define c-association as the maximum association between any two dimensions - or use the determinant of the MINE matrix - TBD

Description

c-association calculates the c-association based on the maximal information coefficient We define c-association as the maximum association between any two dimensions - or use the determinant of the MINE matrix - TBD

Usage

c_association(confs, alpha = 1, C = 15, var.thr = 1e-05, eps = NULL)

Arguments

confs

a numeric matrix or data frame with two columns

alpha

an optional number of cells allowed in the X-by-Y search-grid. Default value is 1

C

an optional number determining the starting point of the X-by-Y search-grid. When trying to partition the x-axis into X columns, the algorithm will start with at most C X clumps. Default value is 15.

var.thr

minimum value allowed for the variance of the input variables, since mine can not be computed in case of variance close to 0. Default value is 1e-5.

eps

integer in [0,1] (?). If NULL (default) it is set to 1-MIC. It can be set to zero for noiseless functions, but the default choice is the most appropriate parametrization for general cases (as stated in Reshef et al). It provides robustness.

Examples

x<-seq(-3,3,length.out=200)
y<-sqrt(3^2-x^2)
z<- sin(y-x)
confs<-cbind(x,y,z)
c_association(confs)

[Package stops version 0.0-40 Index]