c-association calculates the c-association based on the maximal information coefficient We define c-association as the aggregated association between any two columns in confs
c-association calculates the c-association based on the maximal information coefficient We define c-association as the aggregated association between any two columns in confs
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.
Returns
a numeric value; association (aggregated maximal information coefficient MIC, see mine)