Dependence of variance on covariate design in nonparametric link regression

Akifumi Okuno and Keisuke Yano

Statistics & Probability Letters, 2023, vol. 193, issue C

Abstract: This paper discusses a design-dependent nature of variance in nonparametric link regression aiming at predicting a mean outcome at a link, i.e., a pair of nodes, based on currently observed data comprising covariates at nodes and outcomes at links.

Keywords: Similarity learning; Link prediction (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.spl.2022.109716

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