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Activity Number: 198 - Highlights from STAT
Type: Topic-Contributed
Date/Time: Tuesday, August 10, 2021 : 1:30 PM to 3:20 PM
Sponsor: International Statistical Institute
Abstract #317306
Title: Signal Dimension Estimation Using Principal Component Analysis
Author(s): Klaus Nordhausen* and Joni Virta and Sara Taskinen
Companies: University of Jyväskylä and University of Turku and University of Jyväskylä
Keywords: Principla Component Analysis; Dimension Reduction; Order Determination; Dependent Data; Blind Source Separation; Independent Component Analysis
Abstract:

In this work, we develop inferential tools for determining the correct number of signals under a general noisy latent variable model, which includes as a special case, for example, the noisy independent component model. The problem is approached using hypothesis testing, and we provide both a large-sample test and several resampling-based alternatives assuming independent observations as well as under the assumption of serial dependence. Simulations reveal that our suggested approaches keep the desired levels and have good power.


Authors who are presenting talks have a * after their name.

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