Knockoffs for exchangeable categorical covariates

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Dreassi, Emanuela, Pratelli, Luca, Rigo, Pietro
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914971359641600
author Dreassi, Emanuela
Pratelli, Luca
Rigo, Pietro
author_facet Dreassi, Emanuela
Pratelli, Luca
Rigo, Pietro
contents Let $X=(X_1,\ldots,X_p)$ be a $p$-variate random vector and $F$ a fixed finite set. In a number of applications, mainly in genetics, it turns out that $X_i\in F$ for each $i=1,\ldots,p$. Despite the latter fact, to obtain a knockoff $\widetilde{X}$ (in the sense of \cite{CFJL18}), $X$ is usually modeled as an absolutely continuous random vector. While comprehensible from the point of view of applications, this approximate procedure does not make sense theoretically, since $X$ is supported by the finite set $F^p$. In this paper, explicit formulae for the joint distribution of $(X,\widetilde{X})$ are provided when $P(X\in F^p)=1$ and $X$ is exchangeable or partially exchangeable. In fact, when $X_i\in F$ for all $i$, there seem to be various reasons for assuming $X$ exchangeable or partially exchangeable. The robustness of $\widetilde{X}$, with respect to the de Finetti's measure $π$ of $X$, is investigated as well. Let $\mathcal{L}_π(\widetilde{X}\mid X=x)$ denote the conditional distribution of $\widetilde{X}$, given $X=x$, when the de Finetti's measure is $π$. It is shown that $$\norm{\mathcal{L}_{π_1}(\widetilde{X}\mid X=x)-\mathcal{L}_{π_2}(\widetilde{X}\mid X=x)}\le c(x)\,\norm{π_1-π_2}$$ where $\norm{\cdot}$ is total variation distance and $c(x)$ a suitable constant. Finally, a numerical experiment is performed. Overall, the knockoffs of this paper outperform the alternatives (i.e., the knockoffs obtained by giving $X$ an absolutely continuous distribution) as regards the false discovery rate but are slightly weaker in terms of power.
format Preprint
id arxiv_https___arxiv_org_abs_2410_09835
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Knockoffs for exchangeable categorical covariates
Dreassi, Emanuela
Pratelli, Luca
Rigo, Pietro
Statistics Theory
Methodology
62E10, 62H05, 60E05, 62J02
Let $X=(X_1,\ldots,X_p)$ be a $p$-variate random vector and $F$ a fixed finite set. In a number of applications, mainly in genetics, it turns out that $X_i\in F$ for each $i=1,\ldots,p$. Despite the latter fact, to obtain a knockoff $\widetilde{X}$ (in the sense of \cite{CFJL18}), $X$ is usually modeled as an absolutely continuous random vector. While comprehensible from the point of view of applications, this approximate procedure does not make sense theoretically, since $X$ is supported by the finite set $F^p$. In this paper, explicit formulae for the joint distribution of $(X,\widetilde{X})$ are provided when $P(X\in F^p)=1$ and $X$ is exchangeable or partially exchangeable. In fact, when $X_i\in F$ for all $i$, there seem to be various reasons for assuming $X$ exchangeable or partially exchangeable. The robustness of $\widetilde{X}$, with respect to the de Finetti's measure $π$ of $X$, is investigated as well. Let $\mathcal{L}_π(\widetilde{X}\mid X=x)$ denote the conditional distribution of $\widetilde{X}$, given $X=x$, when the de Finetti's measure is $π$. It is shown that $$\norm{\mathcal{L}_{π_1}(\widetilde{X}\mid X=x)-\mathcal{L}_{π_2}(\widetilde{X}\mid X=x)}\le c(x)\,\norm{π_1-π_2}$$ where $\norm{\cdot}$ is total variation distance and $c(x)$ a suitable constant. Finally, a numerical experiment is performed. Overall, the knockoffs of this paper outperform the alternatives (i.e., the knockoffs obtained by giving $X$ an absolutely continuous distribution) as regards the false discovery rate but are slightly weaker in terms of power.
title Knockoffs for exchangeable categorical covariates
topic Statistics Theory
Methodology
62E10, 62H05, 60E05, 62J02
url https://arxiv.org/abs/2410.09835