VSE knjižnice (vzajemna bibliografsko-kataložna baza podatkov COBIB.SI)
  • Choosing the number of factors in independent factor analysis model
    Viroli, Cinzia
    Independent Factor Analysis (IFA) has recently been proposed in the signal processing literature as a way to model a set of observed variables through linear combinations of hidden independent ones ... plus a noise term. Despite the peculiarity of its origin the method can be framed within the latent variable model domain and some parallels with the ordinary Factor Analysis can be drawn. If no prior information on the latent structure is available a relevantissue concerns the correct specification of the model. In this work some methods to detect the number of significant latent variables are investigated. Moreover, since the method defines a probability density function for the latent variables by mixtures of gaussians, the correct numberof mixture components must also be determined. This issue will be treated according to two main approaches. The first one amounts to carry out alikelihood ratio test. The other one is based on a penalized form of the likelihood, that leads to the so called information criteria. Some simulationsand empirical results on real data sets are finally presented.
    Vir: Advances in methodology and statistics = Metodološki zvezki. - ISSN 1854-0023 (Vol. 2, no. 2, 2005, str. 219-229)
    Vrsta gradiva - članek, sestavni del
    Leto - 2005
    Jezik - angleški
    COBISS.SI-ID - 24315485

    Povezava(-e):

    http://mrvar.fdv.uni-lj.si/pub/mz/mz2.1/viroli.pdf

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