singR: Simultaneous Non-Gaussian Component Analysis

Abstract

Implementation of SING algorithm to extract joint and individual non-Gaussian components from two datasets. SING uses an objective function that maximizes the skewness and kurtosis of latent components with a penalty to enhance the similarity between subject scores. Unlike other existing methods, SING does not use PCA for dimension reduction, but rather uses non-Gaussianity, which can improve feature extraction. Benjamin B.Risk, Irina Gaynanova (2021) <doi:10.1214/21-AOAS1466>.

Related Papers

• → Prim�rzerlegung in Steinschen Algebren(1964)32 cited
• → �ber unirationale Scharen auf algebraischen Mannigfaltigkeiten(1966)4 cited
• → Produkttreue Klassen universeller Algebren(1969)1 cited
• Susquehanna Chorale Spring Concert "Roots and Wings"(2017)
• → ИСПОЛЬЗОВAНИЕ ПОТЕНЦИAЛA СОЦИAЛЬНЫХ ПAРТНЕРОВ В ПОДГОТОВКЕ БУДУЩИХ ПЕДAГОГОВ(2024)