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    Robust Scale Estimation for the Generalized Gaussian Probability Density Function

    Dahyot, Rozenn and Wilson, Simon (2006) Robust Scale Estimation for the Generalized Gaussian Probability Density Function. Advances in Methodology and Statistics (Metodolo\vski zvezki), 3 (1). pp. 21-37. ISSN 1854-0031

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    This article proposes a robust way to estimate the scale parameter of a generalised centered Gaussian mixture. The principle relies on the association of samples of this mixture to generate samples of a new variable that shows relevant distribution properties to estimate the unknown parameter. In fact, the distribution of this new variable shows a maximum that is linked to this scale parameter. Using nonparametric modelling of the distribution and the MeanShift procedure, the relevant peak is identified and an estimate is computed. The whole procedure is fully automatic and does not require any prior settings. It is applied to regression problems, and digital data processing.

    Item Type: Article
    Keywords: Robust Scale Estimation; Generalized; Gaussian; Probability; Density; Function;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 15127
    Depositing User: Rozenn Dahyot
    Date Deposited: 14 Dec 2021 16:11
    Journal or Publication Title: Advances in Methodology and Statistics (Metodolo\vski zvezki)
    Publisher: Faculty of Social Sciences of the University of Ljubljana
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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