Sparse NonGaussian Component Analysis

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Non-gaussian component analysis (NGCA) introduced in offered a method for high dimensional data analysis allowing for identifying a low-dimensional non-Gaussian component of the whole distribution in an iterative and structure adaptive way. An important step of the NGCA procedure is identification of the non-Gaussian subspace using Principle Component Analysis (PCA) method. This article proposes a new approach to NGCA called sparse NGCA which replaces the PCA-based procedure with a new the algorithm we refer to as convex projection.

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Statistics Theory, 62G05, 60G10, 60G35, 62M10, 93E10

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http://salesiana.dossiersoluciones.com/handle/123456789/228213

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0904.0430
 http://arxiv.org/abs/0904.0430

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arXiv