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Paper about a new and fast algorithm to compute a curve of confidence upper bounds for the False Discovery Proportion using a reference family with a forest structure
https://github.com/computorg/published-202510-durand-fast

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Paper about a new and fast algorithm to compute a curve of confidence upper bounds for the False Discovery Proportion using a reference family with a forest structure

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# Fast confidence bounds for the false discovery proportion over a path of hypotheses
Guillermo Durand
2025-10-09

### Citation

Guillermo Durand (October 2025). Fast confidence bounds for the false discovery proportion over a path of hypotheses. Computo.

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### Authors’ affiliations

- [Guillermo Durand](https://durandg12.github.io/) (Université Paris-Saclay, CNRS, Inria, Laboratoire de Mathématiques d’Orsay, 91405, Orsay, France)

### Abstract

This paper presents a new algorithm (and an additional trick) that
allows to compute fastly an entire curve of post hoc bounds for the
False Discovery Proportion when the underlying bound
$V_{\mathfrak{R}}^{\ast}$ construction is based on a reference family
$\mathfrak{R}$ with a forest structure à la Durand et al. (2020). By an
entire curve, we mean the values
$V_{\mathfrak{R}}^{\ast}(S_1),\dotsc,V_{\mathfrak{R}}^{\ast}(S_m)$
computed on a path of increasing selection sets
$S_1\subsetneq\dotsb\subsetneq S_m$, $|S_t|=t$. The new algorithm
leverages the fact that going from $S_t$ to $S_{t+1}$ is done by adding
only one hypothesis. Compared to a more naive approach, the new
algorithm has a complexity in $O(|\mathcal K|m)$ instead of
$O(|\mathcal K|m^2)$, where $|\mathcal K|$ is the cardinality of the
family.

Durand, Guillermo, Gilles Blanchard, Pierre Neuvial, and Etienne
Roquain. 2020. “Post Hoc False Positive Control for Structured
Hypotheses.” *Scand. J. Stat.* 47 (4): 1114–48.
.