c_nonmonotonicity {stops}

c-nonmonotonicity calculates the c-nonmonotonicity based on the maximum asymmetric score We define c-nonmonotonicity as the aggregated nonmonotonicity between any two columns in confs this is one of few c-structuredness indices not between 0 and 1

Description

c-nonmonotonicity calculates the c-nonmonotonicity based on the maximum asymmetric score We define c-nonmonotonicity as the aggregated nonmonotonicity between any two columns in confs this is one of few c-structuredness indices not between 0 and 1

Usage

c_nonmonotonicity(
  confs,
  aggr = max,
  alpha = 1,
  C = 15,
  var.thr = 1e-05,
  zeta = NULL
)

Arguments

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 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.

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. SOM). It provides robustness.

Value

a numeric value; nonmonotonicity (aggregated maximal asymmetric score MAS, see mine)

Examples

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