c_association {stops} | R Documentation |
c-association calculates the c-association based on the maximal information coefficient We define c-association as the aggregated association between any two dimensions
c_association(confs, aggr = max, alpha = 0.6, C = 15, var.thr = 1e-05, zeta = NULL)
confs |
a numeric matrix or data frame |
aggr |
the aggregation function for configurations of more than two dimensions. Defaults to max. |
alpha |
an optional number of cells allowed in the X-by-Y search-grid. Default value is 0.6 |
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. |
zeta |
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. |
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)