Scan Clustering: A False Discovery Approach
M. Perone Pacifico, C. Genovese, I. Verdinelli, and L. Wasserman
We present a method that scans a random field for localized
clusters while controling the fraction of false discoveries.
We use a kernel density estimator as the test statistic and correct
for the bias in this estimator by a method we introduce in this paper.
We also show how to combine information across multiple bandwidths while
maintaining false discovery control.