False discovery rate for scanning statistics

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Panning for gold: ‘model‐X’ knockoffs for high dimensional controlled variable selection (2016, methodology): “A consequence of this mismatch is that the result of the analysis may be completely misleading, as beautifully argued in Paciﬁco et al. (2004); Benjamini and Heller (2007); Siegmund et al. (2011), see also Chouldechova (2014) and Brzyski et al. (2016) for later references.”
Panning for Gold: Model-free Knockoffs for High-dimensional Controlled Variable Selection (2016, background): “A consequence of this mismatch is that the result of the analysis may be completely misleading, as beautifully argued in Pacifico et al. (2004); Benjamini and Heller (2007); Siegmund et al. (2011), see also Chouldechova (2014) and Brzyski et al. (2016) for later references.”
Covariate powered cross‐weighted multiple testing (2017, background): “potential advantage of reducing high-frequency components of the noise. Moreover, in such setups, the cluster is the natural unit of discovery, not the individual feature (Benjamini and Heller, 2007; Siegmund et al., 2011). If avoiding dependence by modifying the analysis upstream of the multiple te”