A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Unsupervised linear discrimination using skewness
Tekijät: Radojičić, Una; Nordhausen, Klaus; Virta, Joni
Kustantaja: Academic Press
Julkaisuvuosi: 2026
Lehti: Journal of Multivariate Analysis
Artikkelin numero: 105524
Vuosikerta: 211
ISSN: 0047-259X
eISSN: 1095-7243
DOI: https://doi.org/10.1016/j.jmva.2025.105524
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Osittain avoin julkaisukanava
Verkko-osoite: https://doi.org/10.1016/j.jmva.2025.105524
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/506160615
Rinnakkaistallenteen lisenssi: CC BY
Rinnakkaistallennetun julkaisun versio: Kustantajan versio
It is well-known that, in Gaussian two-group separation, the optimally discriminating projection direction can be estimated without any knowledge on the group labels. In this work, we gather several such unsupervised estimators based on skewness and derive their limiting distributions. As one of our main results, we show that all affine equivariant estimators of the optimal direction have proportional asymptotic covariance matrices, making their comparison straightforward. Two of our four estimators are novel and two have been proposed already earlier. We use simulations to verify our results and to inspect the finite-sample behaviors of the estimators.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
Julkaisussa olevat rahoitustiedot:
The work of JV was supported by the Research Council of Finland (Grants 335077, 347501, 353769). KN was supported by the HiTEc COST Action (CA21163) and by the Research Council of Finland (363261). The work of UR was supported by the Austrian Science Fund (FWF) , [10.55776/I5799].
