Interpretation of low, negative, cubic clustering criterion values

#1
Hello all,

My question is how do you use the cubic clustering criterion to assist in selecting an appropriate number of clusters when the values are all negative?

I know that when they are positive you look for peaks in the values to indicate a demarcation point. However, when they are all negative values do you look then for troughs/low points or still peaks? These negative values are only low (max -3) not excessively high indicating outliers.

I can't seem to find any information on this matter other than on the fact the distribution may be unimodal or long tailed.

Your advice is much appreciated,

Kwak