Optimal Designs for Regression on Lie Groups

Fuente: arXiv
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Main Authors: Chakraborty, Somnath, Dette, Holger, Kroll, Martin
Format: Preprint
Published: 2024
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author Chakraborty, Somnath
Dette, Holger
Kroll, Martin
author_facet Chakraborty, Somnath
Dette, Holger
Kroll, Martin
contents We consider a linear regression model with complex-valued response and predictors from a compact and connected Lie group. The regression model is formulated in terms of eigenfunctions of the Laplace-Beltrami operator on the Lie group. We show that the normalized Haar measure is an approximate optimal design with respect to all Kiefer's $Φ_p$-criteria. Inspired by the concept of $t$-designs in the field of algebraic combinatorics, we then consider so-called $λ$-designs in order to construct exact $Φ_p$-optimal designs for fixed sample sizes in the considered regression problem. In particular, we explicitly construct $Φ_p$-optimal designs for regression models with predictors in the Lie groups $\mathrm{SU}(2)$ and $\mathrm{SO}(3)$, the groups of $2\times 2$ unitary matrices and $3\times 3$ orthogonal matrices with determinant equal to $1$, respectively. We also discuss the advantages of the derived theoretical results in a concrete biological application.
format Preprint
id arxiv_https___arxiv_org_abs_2410_00429
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal Designs for Regression on Lie Groups
Chakraborty, Somnath
Dette, Holger
Kroll, Martin
Statistics Theory
62K05
We consider a linear regression model with complex-valued response and predictors from a compact and connected Lie group. The regression model is formulated in terms of eigenfunctions of the Laplace-Beltrami operator on the Lie group. We show that the normalized Haar measure is an approximate optimal design with respect to all Kiefer's $Φ_p$-criteria. Inspired by the concept of $t$-designs in the field of algebraic combinatorics, we then consider so-called $λ$-designs in order to construct exact $Φ_p$-optimal designs for fixed sample sizes in the considered regression problem. In particular, we explicitly construct $Φ_p$-optimal designs for regression models with predictors in the Lie groups $\mathrm{SU}(2)$ and $\mathrm{SO}(3)$, the groups of $2\times 2$ unitary matrices and $3\times 3$ orthogonal matrices with determinant equal to $1$, respectively. We also discuss the advantages of the derived theoretical results in a concrete biological application.
title Optimal Designs for Regression on Lie Groups
topic Statistics Theory
62K05
url https://arxiv.org/abs/2410.00429