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Peak Detection as Multiple Testing Armin Schwartzman1
 

Summary: Peak Detection as Multiple Testing
Armin Schwartzman1
, Yulia Gavrilov1
, Robert J. Adler2
1
Department of Biostatistics, Harvard School of Public Health
2
Department of Electrical Eng., Technion - Israel Institute of Technology
May 21, 2010
Abstract
This paper considers the problem of detecting equal-shaped non-overlapping uni-
modal peaks in the presence of Gaussian ergodic stationary noise, where the number,
location and heights of the peaks are unknown. A multiple testing approach is proposed
in which, after kernel smoothing, the presence of a peak is tested at each observed local
maximum. The procedure provides strong control of the family wise error rate and
the false discovery rate asymptotically as both the signal-to-noise ratio (SNR) and the
search space get large, where the search space may grow exponentially as a function
of SNR. Simulations assuming a Gaussian peak shape and a Gaussian autocorrelation
function show that desired error levels are achieved for relatively low SNR and are ro-
bust to partial peak overlap. Simulations also show that detection power is maximized

  

Source: Adler, Robert J. - Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology

 

Collections: Mathematics; Engineering