Scan clustering: A false discovery approach
We present a method that scans a random field for localized clusters while controlling the fraction of false discoveries. We use a kernel density estimator as the test statistic and adjust 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.
Volume (Year): 98 (2007)
Issue (Month): 7 (August)
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References listed on IDEAS
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- Cristóbal, J. A. & Alcalá, J. T., 1998. "Error Process Indexed by Bandwidth Matrices in Multivariate Local Linear Smoothing," Journal of Multivariate Analysis, Elsevier, vol. 66(2), pages 207-236, August.
- M. Perone Pacifico & C. Genovese & I. Verdinelli & L. Wasserman, 2004. "False Discovery Control for Random Fields," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1002-1014, December.
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